Prevalence and risk factors of problematic internet use and the associated psychological distress among graduate students of Bangladesh

Problematic Internet use (PIU) or Internet addiction (IA) has been extensively researched since the mid-1990s, particularly in some Western and Asian countries. Although considerable evidence shows that PIU is associated with a number of negative health outcomes in adolescents and adults (Ko et al. 2012; Kuss et al. 2013a), it was not officially classified as a clinical disorder in the latest edition of the Diagnostic and Statistical Manual for Mental Disorders (DSM-V) (APA 2013). This indicates the need for further evidence on this emerging mental health epidemic.

Examining the prevalence and factors of PIU and the associated health problems is particularly important in a country like Bangladesh where the growth of Internet use is faster than socio-economic development itself. In line with global technological development, the use of Internet has also accelerated in Bangladesh, with the number of Internet users increasing from 0.1 million in 2000 to 62 million in 2016 (BTRC 2016). This unprecedented growth of Internet may pose a variety of health challenges, if proper measures are not taken in the right time. Perhaps the most important reason is the unconditional and positive acceptance of its use among common users as well as policy makers. The proliferation of the use of Internet has been largely considered an indicator of development. The government gives tremendous effort to make this happen, that is, to provide each citizen access to Internet with the ultimate aim of building a ‘Digital Bangladesh’ by 2021. Therefore, it is plausible to assume that people as a whole are not aware of the problematic use of Internet and its effects on their psychological health.

PIU has been defined as ‘an individual’s inability to control their internet use, which in turn leads to feelings of distress and functional impairment of daily activities’ (Shapira et al. 2000). It is a condition akin to ‘impulse-control disorder’ that does not involve an intoxicant similar to symptoms of pathological gambling, overeating and so on (Young 2004). Kimberly S. Young was one of the key proponents of the construct ‘Internet Addiction’. She proposed eight diagnostic criteria adapted from the symptoms of pathological gambling (DSM-IV) for detecting an individual’s Internet use as problematic (Young 1996). These are cognitive preoccupation with the Internet, increased tolerance, unsuccessful attempts to decrease use, withdrawal symptoms, staying online much longer than needed, lying about online activity, negative emotion resulting from online activity, and use of the Internet to self-medicate. Clearly, an individual with these symptoms will face difficulty in normal daily functioning and may experience poor mental health. To test this hypothesis, it is crucial for professionals to measure PIU systematically. A number of tools have been developed out of which Young’s internet addiction test (IAT) was found to have wide uses (Young 1998). IAT gives a score ranging between 20 and 100, with a higher score indicating a greater degree of PIU.

Studies examining the prevalence of PIU lack consensus on the diagnostic criteria set to identify PIU due to various measures and cut off points used (Kuss et al. 2013a, b). Considering only Young’s IAT with a cut-off point of 70 and above, a recent meta-analysis of 164 prevalent figures from 31 nations across seven world regions estimated a global prevalence of IA as 6.0% (95% CI 5.1–6.9) (Cheng and Li 2014). This classification of PIU, however, did not consider moderate users who are also unable to control their Internet use (Young 2016). Therefore, incorporating moderate and excessive users as defined by IAT would be safe to detect PIU (i.e., PIU = IAT score 50+). Following this notion, the prevalence of PIU appears to be high. For instance, a recent epidemiological study conducted in six Asian countries revealed the prevalence of PIU as follows: Philippines (51%), Japan (48%), China (19%), Hong Kong (35%), South Korea (14%), and Malaysia (37.5%) (Mak et al. 2014). No such comprehensive investigations have been carried out in Bangladesh, though a preliminary assessment with a small sample of university students (n = 172) found that 36% of the participants scored equivalent to PIU (Nigar and Karim 2014).

The majority of the studies, however, reported the prevalence, predictors and consequences of addictive use of Internet using adolescent samples (e.g., Kuss et al. 2013b; Lam et al. 2009; Liberatore et al. 2011; Yu and Shek 2013). Much less is known about the young adults, notably the university graduates, who are at particular risk of PIU due to several reasons. Firstly, they have comparatively wide and easy access to the Internet via campus laboratory, free campus Wifi Zone and cheap mobile Internet packages. This explains, in part, why 90% of the social media users in the USA belong to the age group 18–29 (Perrin 2015). In Bangladesh, 94% of the total subscribers accessed Internet via mobile phones until April 2016 (BTRC 2016) and obviously, youths are the major consumers of the mobile Internets. Secondly, the youth, irrespective of their living arrangement such as living with family or in university dormitories, typically enjoy the freedom of their choices and Internet use. Next, considering their developmental period in which they are striving to build own identity, career and partner, they may use Internet to facilitate the expected growth, which in turn may appear as an addictive behaviour (Lanthier and Windham 2004). According to Wallace, ‘there is no question that twernty-first century youth have become far more dependent upon connectivity for studying, playing, communicating, and socializing’ (Wallace 2014). Existing literature also demonstrates a prevalence of PIU among university/college students from 0.8% in Italy (Poli and Agrimi 2012) to a moderate level of 18.3% in UK (Niemz et al. 2005) to a higher level of 40% in Jordan (Al-Gamal et al. 2015).

PIU has been found to be associated with a broad range of negative health outcomes with some exceptions. For example, increased depressive symptoms were associated with spending increased time in online activities namely shopping and gambling but inversely with chatting, communication and email (Morgan and Cotten 2003). That is, spending time on social networking was positively associated with mental health. However, recent evidence shows an overall negative relation with online networking and well-being (Sabatini and Sarracino 2014) which indicates that the normal use of Internet could turn into problematic over time. In addition to well-being, PIU was also linked with adolescents’ psychosomatic (i.e., poor physical energy, physiological dysfunction, and poorer immunity), behavioural and emotional symptoms (Cao et al. 2011). Adolescents with PIU are also at risk of relatively high depression and poor social adaptation. Lam and Peng (2010), for example, prospectively examined the effect of pathological Internet use and demonstrated that the adolescents with addictive use of Internet were at a relatively high risk of developing depression in the follow up. Although Internet provides an avenue for easy social interactions, transferring these skills into real life is difficult, as it requires exposures to real life situations. Furthermore, psychiatric co-morbidity of IA has also been well-documented particularly for substance use disorder, attention-deficit hyperactivity disorder (ADHD), depression, hostility, and social anxiety disorder [see Ko et al. (2012) for a review].

Specific studies on PIU and psychological well-being among university students were limited to explaining simple association of these two constructs. For instance, PIU was positively correlated with psychological distress as measured by perceived stress scale (Cohen et al. 1983) in a sample of university students in Jordan (Al-Gamal et al. 2015). Niemz et al.(2005) assessed psychological distress by the 12-items General Health Questionnaire (GHQ-12) and PIU of 371 British students and found that there was no significant difference in the mean score of GHQ-12 among PIU and non-PIU groups [F(2, 368) = 2.15; p = 0.118].

While there is a plethora of research focusing on a general negative association of PIU with psychological well-being, very little is known about the role of the socio-demographic determinants or the lifestyle factors in the association of interest. For example, socio-demographic factors such as age, sex, socio-economic status (SES), relationship status, living arrangements as well as behavioural factors such as smoking, physical activity and sleeping habit are generally found to be associated with overall psychological well-being (Bayram and Bilgel 2008; Glozier et al. 2010; Matsuzaki et al. 2007). Short habitual sleep duration, for instance, has been shown to be linearly associated with persistent psychological distress in young adults (Glozier et al. 2010). Again, a breakup in a committed relationship usually results in symptoms of depression, loneliness and even self-harm tendencies (Rhoades et al. 2011). Furthermore, the lower the SES, the poorer the overall health, popularly known as the social gradient in health (Marmot 2009). In a similar vein, males generally report a higher prevalence of PIU than females (Ha and Hwang 2014; Shahnaz and Karim 2014). These factors, in turn, could play a crucial role in the association between PIU and psychological distress. Therefore, an individual with lower psychological well-being could be the victim of many other factors and not necessarily due to his or her problematic use of Internet. Consequently, an investigation into the association between PIU and psychological well-being with a simultaneous focus on the relevant socio-demographic and lifestyle factors would be a useful contribution.

To our knowledge, only three studies with comparatively small sample sizes focused on IA in Bangladesh (Karim and Nigar 2014; Nigar and Karim 2014; Shahnaz and Karim 2014) but none investigated IA in relation to psychological distress or its socio-demographic and behavioural determinants. The present paper, therefore, is the first of its kind in the context of Bangladeshi society. The paper aims to report the prevalence and risk factors of PIU among young Bangladeshi adults and examine the association between PIU and psychological distress with a particular attention paid to the role of socio-demographic and health behavioural factors in the association of interest. Specifically, the paper addresses the following research questions: (1) What is the prevalence of PIU among the graduate students of Bangladesh? (2) Does the prevalence of PIU differ significantly between different social groups? (3) Is PIU associated with psychological distress independent of the sociodemographic and behavioural factors? (4) To what extent is the association between PIU and psychological distress explained by the socio-demographic and behavioural factors?