Negative Effects of Technology on Socialization

Abstract 

Technology has taken a central role in people lives, and its negative contributions towards the decline in physical interactions have been documented. The objective of this paper is to review evidence that validates the hypothesis that technology, the use of social networking in particular, has deleterious effects on face-face communication. The paper is conceptualization on empirical evidence linking internet addiction with decrease in the levels of physical interactions across different spheres. Therefore, technology and internet consumption trends are examined to understand their significance and relationship to the topic under study. The paper also explores theoretical behavioral models in the context of technology to establish important links between use and associated behavior. Also presented is empirical evidence in support of the hypothesis on the negative role of technology, with emphasis on online social networking sites that are determinants of cellphone and internet addiction in relation to face-face interactions. Finally, the paper briefly reviews overall effects of online dependence syndrome on physical interactions, and concludes by offering suggestions for addressing possible future inevitable impacts.

Introduction 

Understanding the role of technology on socialization needs a historical perspective, starting for instance in 1963 when an American poet, T.S. Eliot, following adoption of television as mainstream media, warned that the platform, allowed millions of people to simultaneously listen to the same joke, and yet remain lonesome. The situation has changed little today with empirical evidence showing that technology is dramatically affecting socialization in the societies. In earlier findings in the survey conducted by the Stanford Institute for the Quantitative Study of Society (SIQSS), it was found out that people who spent more time on the internet were more likely to spend less time interacting with other people in the real world. In fact, Nie and Erbring (2000) observed that the level of face-face interaction with family, friends, and co-workers fell by 24 minutes for very hour one spent using the internet. Criticism about the study designs and methodologies leading to such conclusions exists, but it does not obscure the fact that technology has both positive and negative impacts on socialization. According to Roberts, Pullig and Manolis (2015), application of hierarchical models in studying the use of technology has linked emotional instability, materialism, introversion, and impulsiveness to cellphone and internet addition, therefore, this paper seeks to demonstrate the negative role of technology towards antisocial behavior.

Overview of Trends in the Use of Technology 

Technology has revolutionized socialization among people, and its effects are felt and observed across all facets of life from business organizations, household, family, classroom, to individual levels. It is evident that the exponential rise in the use of technology owes much to the tech savvy generations, specifically the high number of millennials. Anderson and Raine (2012) observed that teens and young adults lead the march towards rapid adoption of mobile internet. “Hyper connected” and “always on” are the common terminologies used to describe the current environment that facilitates continuous linkages through devices, between people and global intelligence. Immersion of teens and youths into the techno world and their ties to the mobile and social aspects of it was noted in a nationally representative survey conducted by the Pew Research Center. The study found out that 95% of teens aged 12-17 spent time online, 76% of them use social networking sites, and 77% were connected using cellphones. In the same vein, 96% of teens aged 18-29 use the internet, 84% use social networking sites, and 97% own cellphones. Over half of teens in those cohorts own smartphones and 23% tablets (Anderson & Raine, 2012). There are concerns that the shift towards communication technologies among this cohort group will expose millennial to both benefits and suffering.

The most significant influencer has been the exponential rise in the use of social networking sites. According to Anderson and Raine (2012), the Pew Research Center established that of the 225 million twitter users at the time, approximately 20 million followed 60 or more accounts and another 2 million followed 500 or more accounts. Similarly, Facebook had over 800 million users spending on average, 700 billion minutes monthly using the social networking site. The users install over 20 million applications daily, and by mid-201, they had uploaded over 100 billion photos on the site. During the same timeframe, YouTube users were uploading 60 hours of videos on the platform every minute, triggering more than 1 trillion playbacks, which translate to approximately 140 video views per person. The trend among teens and young adults point towards a global society tending to communication technologies at the expense of face-to-face interaction.

However, the trend is not limited to the youthful generation because technology is the driving element of life in the 21 st century. The need to remain relevant has seen almost all global societies invest substantial in technology, with the communication sector being at the forefront. According to Poushter (2016), a recent global survey conducted by Pew Research Center revealed that two thirds of the world’s population uses the internet. Though advanced connectivity exists in developed countries, ownership of smartphones and internet usage continue to climb in emerging economies. The global median of adults, who own a smartphone and use the internet, as shown in figure 1 below, is 67% (Poushter, 2016). However, the report also indicates that internet users in emerging economies are frequently use social networking sites compared to those in the US and Europe. One can argue that as the technology use gap between developed and emerging economies narrows, more people will be brought on board towards realization of the goal of making the world a global village. The deleterious effects of such a transitions remain tentative, but one can argue with certainty, based on already existing evidence, that some of them would have substantial negative effects on the levels of face-to-face personal interactions.

Figure 1: Global comparisons of smartphone ownership and internet usage per country (Poushter, 2016).

Theoretical Foundations of Association between Technology and Antisocial Behavior 

The internet and associated technologies have long been questioned as paradoxes for their role in the reduction of social involvement and psychological wellbeing. Kraut, Patterson, Lundmark et al. (1998) prediction on the potential of the internet to change the lives of ordinary citizens as much as the telephone and television did, has come to pass. However, controversy surrounds the lack of consensus on the internet’s potential to improve or harm an individual’s participation in the community life and social relationships. Therefore, it is imperative to examine some of the theoretical foundations on which arguments about antisocial contributions of such technologies are based.

Roberts, Pullig and Manolis (2015) examine the relationship between personality traits and cellphone addiction and established existence of a direct positive association between the central trait of attention impulsiveness and cellphone addiction. Other researchers have explored the existence of such associations driven by motivations to explain the foundations of the roles of technology in aiding antisocial behavior. Attempts have been made to explain the phenomenon from psychodynamics and behavioral perspectives. For instance, Daniel (2006) observed that face-to-face socialization critically reshapes an individual’s brain. They observe that neuroplasticity has the potential to determine the shape, size, number of neurons, and their synaptic connections in a human brain. Simply put, key relationships of an individual can largely alter their neural circuitry; hence collectively help individuals to modify who and how they are. Daniel (2006) advances the concept of emotional economy, which postulates that emotions, attitudes, and feelings can be truly contagious. Socialization plays a key role in defining cognitive function and development due to the neuroplasticity. Therefore, addiction to the internet or cellphone denies an individual the opportunity to socialize, hence impairing with these vital developmental processes.

A host of behavioral models has been linked to adoption of technology. Lai (2017) noted that some of the commonest behavioral model used to predict adoption of technology for different purposes included but are not limited to:

The Theory of Diffusion of Innovations (DIT)

The Theory of Reasonable Action (TRA)

Theory of Planned Behavior (TPB)

Decomposed Theory of Planned Behavior

The Technology Acceptance Model (TAM)

According to Lai (2017), the theories can play a critical role in predicting past, present, and future application and adoption of technology. The theories operate on the precipice of a number of factors such as behavioral beliefs, outcome evaluation, normative beliefs, motivation to comply, attitude, subjective, norms, and behavioral intentions. The interaction between these factors takes into account aspects of the TAM model such as perceived usefulness and perceived ease of use that lead to intention and finally actual usage that can be equated to intention behavior and usage behavior.

For instance, application of the theories by Baker-Eveleth and Stone (2008) revealed that behavioral intentions to implement a new software were predicted by “previous computer experience, ease of system use, and administrator support for the software are linked to behavioral intentions to use the software through self-efficacy and outcome expectancy/usefulness and then attitudes toward the software” (p. 135). De Leo and Wulfert (2013) also examined problematic internet usage and other risky behavior using the theories and established the existence of antecedents that link the use to negative effects of technology. According to De Leo and Wulfert (2013), there was observed prevalence of traditional problem-behavior syndrome characterized by impulsive students with deviant social attitudes and the propensity to use tobacco and illicit drugs. There was also an observed problematic internet behavior syndrome characterized by socially anxious students who also demonstrated high levels of depression, conflicting family ties, propensity towards problematic internet usage.

One can argue that the findings corroborate the association between technology and antisocial behavior. People who engage in such problematic behaviors are more likely to remove themselves from the social circle and become dependent on technology as a getaway. Caplan (2003) explored the link between lonely and depressed individuals and their preference for online interaction and its outcomes. The findings illustrated that preference for internet usage acted as a precursor for negative behavior. The overall assertions that can be drawn from behavioral theories is that psychosocial health predicts the levels of preference for online social networking, which in turn mediates negative outcomes associated with problematic internet usage. Therefore, one can argue that the hypothesis that preference for communication technologies rather than face-to-face communication has a central role in the development of negative effects attributed to problematic internet usage is validated by such findings. This is critical in answering the research question of this paper.

Empirical Evidence on the Negative Role of Technology 

There is a consensus among stakeholders that drastic developments in technology have had dramatic impacts on the way people communicate. Face-to-face interactions are the victim as more and more people continue to embrace technology for online communication. Drago (2015) study on the effects of technology on face-face communication established that thee former negatively impacted both thee quantity and quality of the latter. However, knowledge of the effects of technology on face-face communication has not deterred individuals from adopting the use of technology, including continued use of mobile devices in the presence of others (Drago, 2015, P. 13). Social media has been instrumental in the decline in face-to-face interactions. This collection of online communication channels including Facebook, twitter, WhatsApp, YouTube, Instagram, and Pinterest, are dedicated to community based input, content sharing, and collaboration. People can use these platforms to share memories, reconnect, plan events, and communicate with ease. The introduction of mobile devices and access of such platforms through them eliminated the barrier that limited access to computers. As a result, the number of people who are active in these platforms through mobile devices, particularly smartphones, has risen exponentially over the last few years. Based on the findings by De Leo and Wulfert (2013), one can argue that the number of people exposed to problematic internet use has also risen, and so have antisocial behaviors associated with it.

Cellphone and Internet Addiction 

The prevalence of phone dependence syndrome is determined by the definition of the concept and the scales used to quantify it. The phenomenon has been measure in adults and adolescents using the 20-item self-reported problematic use of mobile phones (PUMP), and the mobile phone problem use scale (MPPUS) (de-Sola, Talledo, de Fonseca et al. , 2017; Tavakolizadeh, Atarodi, Ahmadpour et al. , 2014). Mobile phone overuse is associated with social and psychological problems and poor health. Therefore, cellphone dependence syndrome is always viewed as problematic cellphone use.

The number of studies linking problematic cellphone use to antisocial problems is substantial. The trend cuts across all geographical regions and demographics. de-Sola, Talledo, de Fonseca et al. (2017) observed that overuse of cellphones has risen exponentially in industrialized countries and is linked to behavioral addiction, a non-recognized medical condition. de-Sola, Talledo, de Fonseca et al. (2017) conducted in Spain established four categories of users among adults: casual, regular, at risk, and problematic. High prevalence of use was observed among at risk and problematic users with 15.4% and 5% respectively, implying that 20.5% users had problematic cellphone usage. Almost a similar trend existed among university students. Tavakolizadeh, Atarodi, Ahmadpour et al. (2014) examined the link between the prevalence of cellphone overuse and mental health status and demographic factors among university students from Gonabad University, Iran, and established a 36.5% prevalence rate. In addition, the researchers found a significant relationship between mobile phone usage and mental health status, somatization, anxiety, and depression. However, no significant relationship was observed between the same and social dysfunction, gender, marital status, settlement, or academic achievement. One can argue that the absence of a relationship in the latter can be misleading because evidence shows that mental health status, anxiety, and depression can be antecedents of antisocial behavior.

It is important to note that there is conflicting evidence about the prevalence internet addiction across different demographics. Kuss, Van Rooij, Shorter et al. (2013) established that internet addiction was perceived to be a mental concern among Dutch adolescents with dependence syndrome rated at 3.7%. The study also established that online gaming and use of social applications increased the risk of internet addiction. It is important to note that the prevalence of internet addiction among adolescents was comparatively low to that of adults, implying the former are at a lesser risk of experiencing the negative effects associated with problematic internet use. Kuss, Van Rooij, Shorter et al. (2013) call for inclusion of internet addiction on the DSM-V, implying that its prevalence is gaining recognition among researchers and health practitioners as a recognizable mental problem. Therefore, its contribution towards antisocial behavior is gaining significance, corroborating the hypothesis on the negative effects of technology.

Roberts, Pullig and Manolis (2015) linked aspects such as mental instability, introversion, openness to experience, conscientiousness, materialism, and need for arousal to motor, non-planning, and attention impulsiveness and directly to cellphone addiction. The emphasis placed by this paper on cellphone addiction at the expense of other technologies is informed by evidence showing that these devises are becoming instrumental in people’s daily lives, with majority using them to access social networking sites. Virtual interactions online preoccupy many people and spending too much time online was found to contribute to increased levels of social isolation and antisocial behavior (see figure 2 below).

Figure 2: The relationship between time spent online and the level of social isolation (Nie & Erbring, 2000).

Overall Societal Implications 

Evidence cited in this paper shows that social networking sites accessed through mobile devices are the leading cause of online dependence syndrome. It is important to note that other paradigms of online involvement including gaming exist, but social networking sites represent the most significant because it shares some functionalities with face-to-face communication (Roberts, Pullig, & Manolis, 2015), which it threatens to replace. Therefore, social media can be taken to represent other technologies that have negatively contributed to the decline in the quantity and quality of face-face interactions, specifically given that the manner in which they do so is through social isolation from increased time spent online.

The increasing number of people with smartphones as technology advances towards previously remote regions has significantly decreased the quantity of face-face communication. The prevalence of social media motivates more people to want to interact online rather than in person to avoid inconveniences. The ease and efficiency provided by online platforms may be positive, but it has contributed to development of antisocial behavior as per the theories highlighted in Lai (2017). The global society is becoming more complacent, preferring to spend time behind computers rather than take part in the traditional form of physical social interaction. The absence of intimate conversations with one another in close proximity, also contributes to the declining quality of face-face communication. People with anxiety, depression, and other psychological issues have shifted to finding solace online without being aware that their antisocial behavior is actually harmful to their persona and health. Instant access to news and information cannot be used to justify the demerits of social networking sites.

Today, it is common to find two people sharing a table in a restaurant deeply engrossed with their phones rather than having the luxury of face-face interaction. Evidence shows that approximately 93% of communication is nonverbal; hence, the obsession with online platforms implies people miss out on the important cues that make conversations worthwhile. This can be argued to be the reason behind the marked decline in the amount of relationships forged through physical interactions. In addition, researchers have linked internet addiction to decline in language and communication skills, making individuals unable to sustain a meaningful face-face conversation. There is also the potential of cyberbullying on such platforms, which is likely to exacerbate the situation given that people who prefer online social networks are associated with mental health problems that can worsen upon exposure.

Conclusion 

Technology is here to stay and the only way of solving its negative effects is through development of countermeasures that do not delete its benefits but rather enhance them. It is important for stakeholders to understand that internet addiction cuts across populations and demographics, hence the need for programs that encourage physical social interactions to curb the threat of rising antisocial behavior across global communities. Such programs can be developed based on studies on antecedents of internet addiction among different populations and demographics. It is also important to point out that currently, there is a gap between theory and practice in relation to the negative effects of technology on face-face interactions. Evidence linking the two has been explained from the behavioral perspectives, hence the need for thorough research into the field to validate the hypothesis. This is necessary because the world is yet to feel the real negative effects of technology because some of them are slow maturing. Therefore, it is important to take precautionary and preventive measures to avoid the worst-case scenario where a significant proportion of the world cannot carry a meaningful face-face interaction or conversion in the near future.

References

Anderson, J. & Raine, L. (2012). Main findings: Teens, technology, and human potential in 2020. Pew Research Center. Retrieved from: http://www.pewinternet.org/2012/02/29/main-findings-teens-technology-and-human-potential-in-2020/

Baker-Eveleth, L., & Stone, R. W. (2008). Expectancy theory and behavioral intentions to use computer applications.  Interdisciplinary Journal of Information, Knowledge, and Management ,  3 , 135-146.

Caplan, S. E. (2003). Preference for online social interaction: A theory of problematic Internet use and psychosocial well-being.  Communication research ,  30 (6), 625-648.

Daniel, G. (2006). Social intelligence: The new science of human relationship s. Hutchinson.

De Leo, J. A., & Wulfert, E. (2013). Problematic Internet use and other risky behaviors in college students: An application of problem-behavior theory.  Psychology of addictive behaviors ,  27 (1), 133-141.

de-Sola, J., Talledo, H., de Fonseca, F. R., & Rubio, G. (2017). Prevalence of problematic cell phone use in an adult population in Spain as assessed by the Mobile Phone Problem Use Scale (MPPUS).  PloS one ,  12 (8), e0181184.

Drago, E. (2015). The effect of technology on face-to-face communication.  Elon Journal of Undergraduate Research in Communications ,  6 (1), 13-19.

Kraut, R., Patterson, M., Lundmark, V., Kiesler, S., Mukophadhyay, T., & Scherlis, W. (1998). Internet paradox: A social technology that reduces social involvement and psychological well-being?  American psychologist ,  53 (9), 1017-1031.

Kuss, D. J., Van Rooij, A. J., Shorter, G. W., Griffiths, M. D., & van de Mheen, D. (2013). Internet addiction in adolescents: Prevalence and risk factors.  Computers in Human Behavior ,  29 (5), 1987-1996.

Lai, P. C. (2017). The literature review of technology adoption models and theories for the novelty technology.  JISTEM-Journal of Information Systems and Technology Management ,  14 (1), 21-38.

Nie, N. H., & Erbring, L. (2000). Internet and society.  Stanford Institute for the quantitative study of society ,  3 , 14-19.

Phoushter, J. (2016). Smartphone ownership and internet usage continues to climb in emerging economies. Pew Research Center. Retrieved from: http://www.pewglobal.org/2016/02/22/smartphone-ownership-and-internet-usage-continues-to-climb-in-emerging-economies/

Roberts, J. A., Pullig, C., & Manolis, C. (2015). I need my smartphone: A hierarchical model of personality and cell-phone addiction.  Personality and Individual Differences ,  79 , 13-19.

Tavakolizadeh, J., Atarodi, A., Ahmadpour, S., & Pourgheisar, A. (2014). The prevalence of excessive mobile phone use and its relation with mental health status and demographic factors among the students of Gonabad University of Medical Sciences in 2011-2012.  Razavi International Journal of Medicine ,  2 (1).