Mapping and Auditing Internet Addiction in Technical Education

Mapping and Auditing Internet Addiction in Technical Education

Nana Yaw Asabere, Wisdom Kwawu Torgby, Amevi Acakpovi, Samuel Edusah Enguah, Isaac Ofori Asare
Copyright: © 2021 |Pages: 18
DOI: 10.4018/IJTHI.2021010102
(Individual Articles)
No Current Special Offers


The current proliferation of social networking sites (e.g., Facebook), electronic devices (e.g., smartphones and tablets), and the internet has paved the way for a charge in promoting the phenomenon of internet addiction (IA). This paper analyzed and examined the validity and appropriateness of a well-established instrument for measuring IA among technical education students in Ghana, specifically students of Accra Technical University (ATU). Using a quantitative research method involving questionnaires, data collected from 260 (n=260) students in ATU was used to validate the research objectives and also measure the levels of IA among the students. The principal component tool in statistical package for social sciences (SPSS) was employed to analyze the received data. Analytical results of the study showed that a sizeable majority of students in ATU, especially male students, suffer frequent addiction problems due to the use of the internet. Additionally, results of the study showed that IA psychometric constructs in the Western world differ from those in the African context.
Article Preview

1. Introduction

Globally, the current increased dependence on Information and Communication Technologies (ICTs) has enhanced personal communication and organization performance as a result of excessive and compulsive technology use (Nath, Chen, Muyingi, & Lubega, 2013). Additionally, the current prevalence and proliferation of the internet has introduced the concepts of information overload and big data in smart communities (Xia, Asabere, Ahmed, Li, & Kong, 2013). Previous research studies have suggested and emphasized that technology addiction, which is defined as “an obsessive pattern of IT/ICT-use behaviors and IT/ICT-seeking that takes place at the expense of other important activities,” leads to negative psychological, behavioral and cognitive consequences (Turel, Serenko, & Giles, 2013). Internet Addiction (IA), which is a component of technology addiction, refers to an extreme and uncontrolled need to use the Internet (Nath et al., 2013; Yellowlees & Marks, 2007; Widyanto, Griffiths, & Brunsden, 2011). IA is found to be prevalent among young adults and has the potential to negatively affect a person’s health, effectiveness, happiness and relationships (Nath et al., 2013; Young, 1998a; Yellowlees & Marks, 2007; Widyanto et al., 2011).

Unfortunately, IA often occurs undiagnosed, is difficult to diagnose and is frequently denied by addicts due to the fact that utilization of the Internet is often patronized at work and school (Yellowlees & Marks, 2007; Young, 1998a; Young, 1998b; Young, 1999). The factor involving time spent online has been found to be a strong and positive correlation for IA. Nevertheless, research has shown that time is not the only indicator of problematic use of the internet (Young, 1998a; Young, 1998b; Young, 1999; Widyanto & McMurran, 2004; Griffiths, 2000a; Griffiths, 2000b; Šmahel & Blinka, 2012). In order to corroborate this fact, Widyanto et al. (2011) identified three other underlying factors that collectively define IA. These include (i) mood modification, (ii) psychological/emotional conflict and (iii) time management.

The first factor, mood modification, which is quite troubling, suggests that individuals with IA tend to develop other emotional problems such as moodiness, depression and anxiety in the absence of the Internet (Widyanto et al., 2011). The research finding of Niemz, Griffiths and Banyardin (2005) illustrated that IA was linked to lack of social inhibition and low self-esteem. The second factor, psychological/emotional conflict refers to a person’s preference of being online rather than other social activities such as spending time with family and friends (Widyanto et al., 2011). The third factor, time management (which is the commonest) shows that individuals with IA choose to spend time online at the cost on neglecting other responsibilities and decreased productivity (Widyanto et al., 2011).

In another study, Whang, Sujin and Chang (2003) examined and analyzed the psychological profiles on Internet addicts and suggested that people who are addicted to the Internet usually try to escape from reality than those who are not addicted. Evidence from (Nath et al., 2013; Widyanto et al., 2011; Whang et al., 2003) confirmed that the impact of the IA goes beyond reduced productivity and has profound implications to the psychological well-being of individuals and stability of social units.

Complete Article List

Search this Journal:
Volume 20: 1 Issue (2024)
Volume 19: 1 Issue (2023)
Volume 18: 7 Issues (2022): 4 Released, 3 Forthcoming
Volume 17: 4 Issues (2021)
Volume 16: 4 Issues (2020)
Volume 15: 4 Issues (2019)
Volume 14: 4 Issues (2018)
Volume 13: 4 Issues (2017)
Volume 12: 4 Issues (2016)
Volume 11: 4 Issues (2015)
Volume 10: 4 Issues (2014)
Volume 9: 4 Issues (2013)
Volume 8: 4 Issues (2012)
Volume 7: 4 Issues (2011)
Volume 6: 4 Issues (2010)
Volume 5: 4 Issues (2009)
Volume 4: 4 Issues (2008)
Volume 3: 4 Issues (2007)
Volume 2: 4 Issues (2006)
Volume 1: 4 Issues (2005)
View Complete Journal Contents Listing