Research paperPrevalence, correlates, and network analysis of Internet addiction symptoms among Chinese pregnant and postpartum women
Introduction
Internet addiction, which is defined as ‘an inability to control Internet use, or a maladaptive pattern of Internet use, usually time-consuming, that results in clinically significant impairment or distress’ (Laconi et al., 2014; Young, 2004), typically occurs in adolescents and younger adults. In the past decade, with the common use of Internet across most age groups (Durkee et al., 2012) for information, entertainment and social interaction purposes (The Lancet, 2018), excessive / problematic Internet use and Internet addiction have increased. There is presently much attention on their negative physical and psychosocial consequences (Andreetta et al., 2020; Mamun et al., 2020; Stavropoulos et al., 2021), such as asthenopia (Huang et al., 2005), carpal tunnel syndrome (Duan et al., 2013; Middleton and Anakwe, 2014), psychosomatic symptoms (Cao et al., 2011), negative interpersonal relationships (Milani et al., 2009), personality deviations (Huang et al., 2005), reduced quality of life (QOL) (Ferrara et al., 2017; Van Den et al., 2018), and increased risk of insomnia, cognitive decline, depression, and even suicidal ideation (Huang et al., 2020; Karimy et al., 2020; Lu et al., 2018; Wang et al., 2019).
With the growing research interest in Internet addiction, more than 40 instruments on Internet addiction have been developed (Laconi et al., 2014). However, to date no consensus has been reached on the gold standard for measuring Internet addiction (Laconi et al., 2014). Of the currently available tools on Internet addiction, the Internet Addiction Test (IAT) with 20 items (Young, 1996) is most frequently used. The associated factors of Internet addiction have been widely studied, with commonly reported factors including older age, personality traits, substance abuse, social anxiety, and urban residence (Li et al., 2018; Zajac et al., 2017). For example, individuals having poor relationships with friends or family (Milani et al., 2009) and those with limited parental care were at higher risk of developing Internet addiction (Yen et al., 2007). Internet addiction is also associated with psychiatric comorbidities such as anxiety, depression, and attention deficit and hyperactivity disorder (ADHD) (Ho et al., 2014).
Compared with other subpopulations, pregnant and postpartum women have an increased risk of developing excessive Internet use and Internet addiction, probably due to longer hours being at home (i.e., on maternity leave) and less outdoor and physical activities owing to restricted mobility. Additionally, psychiatric comorbidities (i.e. anxiety, and depression) are common in pregnant and postpartum women (Kazemi and Dadkhah, 2020; Lagadec et al., 2018), which could also increase the likelihood of Internet addiction among this population.
In order to develop effective interventions and allocate health resources to prevent the negative health outcomes of Internet addiction, it is important to understand the prevalence and associated factors of Internet addiction among different populations. As most research on Internet addiction have focused on children and adolescents (Li et al., 2018; Zhang et al., 2018), there is a paucity of studies of Internet use behaviors among other subpopulations such as perinatal women. Further, the epidemiology of Internet addiction is substantially influenced by sociocultural and economic factors, which can result in variations across countries. Currently, no studies on the prevalence and correlates of Internet addiction in perinatal women in China have been published. Although one study (Huang et al., 2018) found that smartphone addiction was significantly associated with depression among women in early pregnancy, such findings could not be generalized to Internet addiction.
Network analysis is a novel data-driven approach that provides a visual depiction of the complex associations among individual symptoms (Beard et al., 2016). It allows identification of highly central symptoms (defined as nodes) and symptom-symptom interactions (defined as edges), and produces spatially ordered networks in which key nodes are located at the center of the network and nodes with fewer connections at the periphery (Mullarkey et al., 2019). Analyzing Internet addiction symptoms from the perspective of network analysis allows better understanding of which symptoms might be particularly central to the experience of Internet addiction (Borsboom, 2017). Furthermore, identifying central nodes and the relevant influential edges may be helpful to develop effective treatment and improve health outcomes (Hofmann et al., 2016).
In this study we examined the prevalence, correlates, and network structure of Internet addiction symptoms (Internet addiction hereafter), and also explored the association of Internet addiction and QOL in Chinese pregnant and postpartum women. According to previous findings (Ferrara et al., 2017; Van Den Eijnden et al., 2018) we hypothesized that certain clinical variables, such as pregnancy stage, and physical comorbidities, would be significantly associated with internet addiction. We also hypothesized that Internet addiction would negatively influence pregnant and postnatal women's QOL.
Section snippets
Study settings, inclusion, and exclusion criteria
This cross-sectional, multicenter study was conducted from February to October 2019. A consecutive sampling method was adopted to recruit participants from eight hospitals located in 8 provinces in China including Beijing, Xinjiang, Sichuan, Liaoning, Guangdong, Qinghai, Hubei, and Jiangsu. Women who met the following criteria were included: 1) adults (aged 18 years or above); 2) fluent in Mandarin or Cantonese, 3) being in the perinatal period (from the start of pregnancy to 1 week after
Participant characteristics
Overall, 1,140 women were invited to take part in this study, and finally, 1,060 met the study entry criteria and completed the assessment, giving a participation rate of 92.98%. The mean age of the women was 29.4 years (SD=4.2). Most of the participants lived in urban areas (n=897, 84.6%), had education at college level or above (n=712, 67.2%), were currently employed (n=655, 61.8), and had their first pregnancy/birth (n=608, 57.4%). Majority of the women did not report adverse pregnancy
Discussion
To the best of our knowledge, this was the first study that examined the prevalence, correlates, and network structure of Internet addiction, and its association with QOL in pregnant and postpartum women. In this study, we found that a total of 320 (30.19%; 95% CI=27.42%-32.96%) pregnant and postpartum women reported Internet addiction. No similar studies in pregnant and postpartum women were conducted, therefore direct comparisons could not be made. When compared to findings in other
Funding source
The study was supported by the National Science and Technology Major Project for investigational new drug (2018ZX09201-014), the Beijing Municipal Science & Technology Commission (no. Z181100001518005), and the University of Macau (MYRG2019-00066-FHS).
Ethical approval and consent to participate
This study was approved by the Clinical Research Ethics Committee of the Peking Union Medical College Hospital and all participating hospitals (Ref No: S-K1273). All participants provided informed consent form.
Authors’ contribution
Study design: HXB, and YTX. Data collection, analysis and interpretation: PHW, XHL, LNG, WXL, YX, YLX, FJL, XJX, and HHW. Drafting of the manuscript: YY, DYZ, YLL, and MZ. Critical revision of the manuscript: TC, and CHN. Approval of the final version for publication: all co-authors.
Consent for publication
Not applicable.
Code availability
Not applicable.
Declaration Competing of Interest
The authors declare that they have no competing interests.
Acknowledgements
None.
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These authors contributed equally to this work.