In the last decade, a new trend in research regarding problematic and/or ‘addictive’ use of smartphones has experienced proliferation. To the best of our knowledge, very few studies to date have examined the relationship between PSU and academic anxiety, academic procrastination, self-regulation or subjective well-being. These recommendations formed the basis for developing and testing a conceptual model of the relationship of PSUs with such factors in this study. A paper-based questionnaire was administered to a sample of 475 Chinese university students during class breaks. In this present questionnaire, a package of psychometric scales is used in the Chinese versions of the study variables, including academic anxiety, academic procrastination, self-regulation, life satisfaction, and PSU. The hypothetical model was tested for validation. The overall fit of the model was fair with the results: CFI = 1.00, RMSEA = 0.008; PSU predicted academic delay and academic anxiety at β = 0.21, p < 0.001 and β = 0.18, p < 0.01, respectively. Instead, it may predict the following: PSU β = – 0.35, p < 0.001; Academic Anxiety β = – 0.29, p < 0.001; Academic Delay β = 0.23, p < 0.001; and life satisfaction, β = 0.23, p < 0.001. Finally, PSU mediated the relationship between self-regulation and academic anxiety or academic procrastination. This has expanded our conceptualization of the problematic use of smartphones regarding study and psychological as well as psychological well-being of higher education students.
Statista n.d. As of 2016, 62.9% of the world’s population has a mobile phone and according to the report, it is 67% in 2019. Compared to this average percentage, many more people in China own mobile phones. According to the Ministry of Industry and Information Technology of the People’s Republic of China, at the end of November 2017, there are approximately 1.42 billion mobile phone users in China; However this would not only account for smart phones being the core of the research study (Ministry of Industry and Information Technology of the People’s Republic of China, 2018). This survey, based on Posture, reports that as of 2015, smartphone usage has already reached 58% of Chinese people. Meanwhile, despite the fact that mobiles and especially smartphones have all the advantages related to the field of communication and access to information, it is increasingly seen that they can have adverse effects and for a small subgroup of users a can become problematic activity—for example, Bianchi and Phillips 2005; Billieux et al 2015a; Carbonell et al 2012; Hussain et al 2017; Lopez-Fernandez et al 2017. A number of symptoms of problematic smartphone use have been established, for example, compulsive seeking behaviours, such as over-checking for new messages, inappropriate use situations, including smartphone use while driving (Billieux et al 2015a).
There are also some signs that problematic smartphone use could become a troubling issue, particularly in China. For example, a study analyzed by Long et al (2016) brings out results that show that the findings presented in that particular research show that problematic use of smartphones among undergraduate students in Mainland China at a prevalence of 21.3% was reported, which is much higher than its proportion in comparable samples taken from other Asian regions such as South Korea at 11.4% and Taiwan at 16.4%–16.7%. They all used the same measurement scale (Problematic Cellular Phone Use Questionnaire, PCPUQ, Yen et al. 2009), the same diagnostic criteria. What could be the reasons for such differences? Still unknown. However, studies conducted in China over the past years also indicate that serious smartphone use is highly correlated with such negative psychological well-being as anxiety and loneliness among college students. 2016. It would therefore be interesting to know whether Chinese university students have a higher prevalence rate of problematic smartphone use and whether this has something to do with less favorable psychological outcomes for the respective group. The purpose of the present study was to design and analyze the relationship between problematic smartphone use and some potential correlates related to student life, including academic anxiety, academic procrastination, self-regulation, and life satisfaction.
Problematic Smartphone Use
Since Griffiths’ article on ‘technological addictions’ in 1995, many authors have referred to the problematic use of mobile phones or the Internet as a form of addiction through terms such as ‘mobile phone addiction’, ‘smartphone addiction’, and ‘Internet addiction’. accepted as such (e.g. Griffiths 2000; Hong et al. 2012; Liu and Kuo 2007; Vidyanto and Griffiths 2006; Young 1998a, b). Such terminology has its origins in the ‘definition of technological addiction’, which is ‘non-chemical (behavioral) addiction that involves human-machine interaction’ (Griffiths 1995, p. 15). However, at the time of writing, diagnostic criteria for mobile phone addiction are not included in the most recently published fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5; American Psychiatric Association, 2013), although Internet One form of use disorder, Internet gaming disorder, is covered in Section 3. It is considered an emerging disorder and is classified as a behavioral addiction like gambling disorder by the American Psychiatric Association 2013. Therefore, most of the work in this area was based on diagnostic criteria for substance dependence and/or pathological gambling (Kuss et al. 2014). Billieux et al. (2015b), the behavior is too simplistic to date However, Griffiths (2005, 2017) maintain the position that any activity that constitutes all the core characteristics of addiction – for example, salience, conflict, tolerance , relapse, mood changes and withdrawal symptoms – should be classified as such. In a highly complex model, Billieux et al. (2015a) proposed a pathway model with a theoretical framework to underline the complexity in problematic mobile phone use behavior with addiction symptoms and psychological factors such as anxiety symptoms and self-control.
This study follows the same approach and focuses on the psychological correlates of problematic smartphone use. Since Chinese undergraduate students report incredibly high penetration of smartphone use – 99.2%, according to Long et al., 2016 this is higher than the use of mobile phones – i.e. Wi-Fi enabled mobile phones – more. and this concept will be referred to as ‘problematic smartphone use’ (PSU). Academic Anxiety and PSU Most empirical studies conclude by saying that anxiety accompanies high levels of smartphone use, which then extends to addiction and what is most commonly referred to as ‘smartphone addiction’ (e.g. Akin Iskender 2008; Leung et al. 2014.
Other research studies with Chinese university students were particularly influential in building a link between anxiety and PSU (Huang et al. 2013; Long et al. 2016). Another conceptual framework contributed to the establishment of the anxiety-PSU link (Billeux 2012; Billieux et al. 2015a) as well as pathological Internet use (Davis 2001). Additionally, it is consistent with trait-situation anxiety theory, which posits that the perception of a threatening situation on the part of an individual can lead to behavioral responses. Such responses may serve as coping tools in controlling the level of anxiety that occurs before the actual threat. However, empirical studies regarding the relationship between PSU and anxiety are mixed, particularly with respect to the direction of the relationship.
For example, one determined that more frequent use of a mobile phone predicted higher levels of anxiety, although the effect size is not strong (Lepp et al. 2014). However, one study showed that the greater the anxiety, the more frequently reported mobile phone use. The problems of lack of clarity about the direction of effects cannot be minimized when conducting correlational research. Indeed, these issues are further complicated by the fact that Lu et al. (2011) stated that text messaging dependence and Internet dependence are not related to anxiety. Other studies that define problematic technology use as ‘addiction’ further show that anxiety will predict mobile phone addiction and Internet addiction (Zboralski et al. 2009; Fu et al. 2010), but also that these variables can predict anxiety (Akin and Iskender 2011), which may indicate a possible two-way relationship. Most of the above research has been conducted with university students, although very little has focused on academic-related anxiety.
Since academic anxiety hinders students’ learning and performance, it seems relevant to question whether this type of anxiety is associated with PSU. Following the control-value theory proposed by Pekrun (2006), a general theoretical model can be described to study academic anxiety, but this theory hypothesizes that academic anxiety may be associated with LS and SR. Based on the above findings, it is believed that PSU at least partially reflects a failure in self-regulation and is even reportedly associated with the use of learning strategies. Therefore, based on the purpose of the present study, the correlation of PSU with academic anxiety of college students in China was explored in the following study.
Academic Delay and PSU
Steele defines procrastination as ‘voluntarily delaying a desired action, even when the delay is expected to make the situation worse’ (p. 7). The concept of academic procrastination is a universal phenomenon, and it has been indicated that students begin to procrastinate as they approach their academic tasks—for example, Clasen et al. 2009; Ley and Silverman 1996. Over the past few years, researchers have given greater importance to this specific relationship between Internet use and academic procrastination. For example, it was found that students who had higher usage rates of social networking through Facebook were also associated with higher rates of academic procrastination (Sahin 2014). Again, in another study conducted, it was found that problematic Internet use was not related to academic procrastination with any statistically significant measure (Odassi 2011). However, in this regard, there is some uncertainty, and, certainly, the relationship between academic procrastination and PSU among Chinese college students would be interesting, as smartphones may be perceived as a means of distraction and thus procrastination. can be considered encouraging. In fact, there was no empirical research specifically focused on the academic procrastination of PSU and college students. Indeed, Schra et al. The PSU delay model based on 2007 also did not consider any such relationship. In such a case, it is also of utmost importance to further explore the nature of such relationship between PSU and academic delay.
More importantly, although most of the studies were conducted in school settings, study results indicate that test anxiety or generalized test anxiety is related to procrastination. As mentioned earlier, it also shares a valid cognitive representation of anxiety with other maladaptive features of academic procrastination, which is similar to fear of failure (Zeidner 1998). Theoretically and empirically sound arguments were also given for the relationship between anxiety and procrastination. Given the above relationship between PSU, it is also interesting to ask whether anxiety might mediate any relationship between PSU and academic procrastination.
Self-Regulation and PSU
Self-regulation is the process by which a person can regulate his or her goal-oriented activities over time and in changing contexts. He defines them as “the internal and/or transactional processes that enable individuals to control their goal-directed activities under circumstances (contexts) that change over time” (1993, p. 25 ). Billieux et al. For the pathway model developed by (2015a), mobile phone use was associated with impulsivity which was interpreted as indicative of failure of self-regulation. However, this pathway conflicts with several studies that predicted lower levels of self-regulation predicted greater Internet or mobile phone use, which could result in harmful outcomes such as anxiety (LaRose and Eastin 2004; LaRose et al. 2003; Soror et al. 2012). Negative pathways were activated to predict negative mobile phone use by samples from Europe based on low levels of self-regulation (Gökerslan et al. 2015; van Deursen et al. 2015). Whether this is also true for mainland Chinese college students is yet to be determined.
Life Satisfaction and PSU
Many studies have analyzed it and it is generally referred to as one of the most important components of subjective well-being (Diener et al. 2002). Many authors have discussed empirical works regarding life satisfaction and PSU, resulting in a large variety of results. For example, Lepp et al found that mobile phone use was not directly and statistically related to life satisfaction or texting among US citizens. Nevertheless, they established the fact that mobile phone use and texting predict GPA and anxiety, and from the results of this study it was found that GPA and anxiety predict a lot in terms of life satisfaction. For example, in the second experiment, life satisfaction was not clearly associated with smartphone addiction, even though the predictor was a type of smartphone addiction that was predicting stress and GPA and potentially also powerfully predicting life satisfaction. Could have done. Yet PSU was related to life satisfaction but negatively affected by Facebook use in multicultural samples (Deyapoglu et al. 2016; Cross et al. 2013). To my knowledge, no study has tried to explore the relationship between PSU and life satisfaction in relation to Chinese mainland university students. Either way, perhaps it is time to empirically examine whether PSU reduces the life satisfaction of Chinese college students.
Objectives and Visions
Clearly, from the above theoretical and empirical literature, there are questions that should be explored based on empirical research, especially in the context of Chinese universities. Given the existence of PSU and its interrelationship with academic anxiety, academic procrastination, self-regulation, and life satisfaction among Chinese university students, this study will be helpful to explore it. There will be six hypotheses, namely: (i) problematic smartphone use will positively predict academic anxiety; (ii) academic anxiety will positively predict academic delay; (iii) problematic smartphone use will predict academic delay; (iv) problematic smartphone use will positively predict academic procrastination mediated by academic anxiety; (v) self-regulation will be a negative predictor of problematic smartphone use and (vi) problematic smartphone use will be a negative predictor of life satisfaction.
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