• Users Online: 619
  • Home
  • Print this page
  • Email this page
Home About us Editorial board Ahead of print Current issue Search Archives Submit article Instructions Subscribe Contacts Login 


 
 Table of Contents  
GUEST EDITORIAL
Year : 2021  |  Volume : 37  |  Issue : 3  |  Page : 245-247

Screen use and behavioral addiction: Making the “porridge” healthy


1 Department of Psychiatry and National Drug Dependence Treatment Centre, All India Institute of Medical Sciences, New Delhi, India
2 Department of Child and Adolescent Psychiatry, National Institute of Mental Health and Neurosciences, Bengaluru, Karnataka, India

Date of Submission16-Sep-2021
Date of Acceptance16-Sep-2021
Date of Web Publication30-Sep-2021

Correspondence Address:
Shekhar Seshadri
Department of Child and Adolescent Psychiatry, National Institute of Mental Health and Neurosciences, Bengaluru, Karnataka
India
Login to access the Email id

Source of Support: None, Conflict of Interest: None


DOI: 10.4103/ijsp.ijsp_272_21

Rights and Permissions

How to cite this article:
Bhargava R, Seshadri S. Screen use and behavioral addiction: Making the “porridge” healthy. Indian J Soc Psychiatry 2021;37:245-7

How to cite this URL:
Bhargava R, Seshadri S. Screen use and behavioral addiction: Making the “porridge” healthy. Indian J Soc Psychiatry [serial online] 2021 [cited 2021 Dec 8];37:245-7. Available from: https://www.indjsp.org/text.asp?2021/37/3/245/327296



The landmark case study by Young[1] and Griffiths[2] paper on “Technological Addiction” marked the advent of a new phenomenology. As expected, it initiated a plethora of empirical research articles on the various aspects of Internet addictions while focusing on epidemiology, case studies, psychsocial determinants, biological factors, psychiatric comorbidities, validation of tools to assess Internet addiction, and so forth. Over the last decade, as these addictions were observed to be rampant globally, different terminologies emerged related to addiction to smartphones, social media use, screen time, gaming, and Internet. Although the term “internet addiction” was most frequently used and researched, the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition placed “Gambling” as having a distinct category and “Gaming” as a condition warranting further study. Besides “Gambling disorder,” International Classification of Diseases 10 did recognize “Gaming” (offline and online) as a separate entity in the classificatory system. However, the terms “technology addiction,” “internet addiction,” “problematic internet use,” “mobile addiction,” “screen addiction,” etc., still remain in wide usage in research. Differences in terminology, diagnostic criteria, assessment tools, and design have led to the variation in prevalence rates. Despite wide differences among studies, behavioral addiction has been seen to be most prevalent among adolescents, especially during COVID.[3]

Much of the literature has examined potential correlates of Internet addiction. Besides focusing on neuroimaging and biochemical changes associated with intensive use of devices, little research has gone into understanding the developmental changes due to Internet addiction from childhood to adolescence, even though the trajectory shows a significant rise.[4] In addition, complications in psychological, physical, and social realms arising due to problematic Internet use have consistently been documented among children and adolescents.[5] However, there is a lack of clarity regarding its bidirectionality.

Technological advancement ensured 3As, i.e., availability, accessibility, and anonymity and sparked a public health concern as the Internet and extensive use of devices (smartphones, tablets, and computers) became a necessity among adolescents for all important activities of daily life. As online learning gradually replaced traditional education in the west, physical, and psychological impact[6] including academic achievement became the focus even before the onset of COVID. Traditional teaching when compared with online teaching in school students failed to identify online teaching as a major risk factor for problematic internet use,[7] but such studies have been sparse. There is a lack of robust evidence as to how pedagogical use of technologies is associated with addiction and other related adverse effects.

In India, online teaching in academic institutions became a norm due to the pandemic. Although the “digital divide” became more marked, technology has proved to be panacea, especially for school-going children. With the closure of academic institutions and lockdown, the only link that sustained education among students, especially for those whose families migrated to distant places was none other than the internet. For the downtrodden families who are devoid of smartphones and the Internet, the Ministry of Human Resource Development developed “Pragyata”[8] that provided a road map for teachers, parents, and children for digital education. Different programs for the online platform (e.g., Diksha) and offline platform (e.g., SWAYAM Prabha on TV, etc.) were initiated to reach out in remote areas. Thus, the increase in “screen time” was inevitable among children and adolescents. The proliferation of mobile digital technology across all the sections of society has also enhanced online time for entertainment, socialization, and information.

The term “Screen time” was initially used to describe the number of times a movie star's face appeared in a particular movie, but it changed its connotation when it was repurposed in 1991,[9] in an article about children's time on TV and video games. Over the years, the concept was used with different phrases (e.g., media use, screen use, digital engagement, etc.), largely in context with young children and technology use. Screen time, in its simplest form, was perceived as “time spent using a device such as a computer, television, or games console.”[10] The focus was on setting limits for young children's screen time and identifying “cutoffs.” Many professional organizations in both the western (e.g., WHO,[11] American Academy of Pediatrics[12]) as well as in the Indian context (e.g., Indian Association of Pediatrics[13]) recommended different cutoffs for different age groups, but these were arbitrary cutoffs based primarily on the less is the better hypothesis.

The focus on-screen time in research significantly gained momentum with the pandemic as COVID- 19 changed the way children and adolescents would play, work (study), and socialize. Internet-based applications and devices compensated for social and emotional needs which arose due to mandatory precautionary measures. Undoubtedly, extended screen time became a challenge for educators and parents while dealing with young children and adolescents.

The issues surrounding the concept “Screen time” came under urgent scrutiny and were no longer considered unidimensional. The studies started interrogating the emphasis placed on “time.” WHO[11] took cognizance of the complexity which is reflected in the definition “Time spent passively watching screen-based entertainment (TV, computer, and mobile devices)” and excluded active engagement. However, the conceptual issues have remained chaotic, and conclusions appear farfetched. Studies which are largely cross-sectional have used different measures to capture “screen time” and lack methodological rigor.[14]

Screen time has been categorized into five types: passive (e.g., watching a movie), interactive (playing games), social (e.g., chatting or facetiming), educational (online class), and others. The different types of screen time have been examined in relation to the mental health and well-being of adolescents. The emerging findings may not be conclusive due to inconsistencies, yet they are important for having been conducted on a large sample[4],[15] or having a longitudinal design.[4],[16] The linear relationship was seen between total time and outcomes but varied with the type of screen activity. Passive screen time was seen to yield the worst outcomes as compared to interactive screen time. The curvilinear trend between digital technology and well-being was the basis for replacing displacement hypothesis[17] with the Digital Goldilock hypothesis,[15] i.e., the posit that increased exposure to technology was harmful because it replaces alternate beneficial activities, was not supported; rather, moderate exposure was associated with positive mental well-being. Longitudinal evidence is inadequate to be able to comment on the outcome in terms of different types of screen activities but then considering the changing nature of the concept, it poses a challenge to understand the complex relationship with addiction and mental health over time. Screen time has been taken as an important index for Internet addiction, but it's time to look beyond “time” to examine issues surrounding “screen.”

The impact of technology even after the pandemic will be long-lasting. Several concerns need to be addressed with the “new normal” to prevent rise in behavioral addiction. The complexity of behavior addiction that encompasses due to varied activities and devices requires a shift in focus: to move beyond routine surveys and cross-sectional studies to the understanding of the process.

The continued reliance on technology among children and adolescents compels us to strike a “screen-life” balance. Each action, whether of a parent, teacher, or of policy-makers, needs to be based on an understanding of the complex relationship between screen, addiction, and wellbeing. The evidence suggests replacing screen “time” with “use” which has an underlying connotation of “moderation” and “content”. Undoubtedly, Goldilocks' penchant for her “medium” porridge has not faded. However, the said parameter is not sufficient to be risk-free. Today, the porridge also needs to be rich in “content” to promote physical and mental health.



 
  References Top

1.
Young KS. Psychology of computer use: XL. Addictive use of the Internet: A case that breaks the stereotype. Psychol Rep 1996;79:899-902.  Back to cited text no. 1
    
2.
Griffiths MD. Technological addictions. Clin Psychol Forum 1995;76:14-9.  Back to cited text no. 2
    
3.
Siste K, Hanafi E, Sen LT, Murtani BJ, Christian H, Limawan AP, et al. Implications of COVID-19 and lockdown on internet addiction among adolescents: Data from a developing country. Front Psychiatry 2021;12:665675.  Back to cited text no. 3
    
4.
Hsieh YP, Hwa HL, Shen AC, Wei HS, Feng JY, Huang CY. Ecological predictors and trajectory of internet addiction from childhood through adolescence: A nationally representative longitudinal study. Int J Environ Res Public Health 2021;18:6253.  Back to cited text no. 4
    
5.
Lissak G. Adverse physiological and psychological effects of screen time on children and adolescents: Literature review and case study. Environ Res 2018;164:149-57.  Back to cited text no. 5
    
6.
Melo C, Madariaga L, Nussbaum M, Heller R, Bennett S, Tsai CC, et al. Educational technology and addictions. Comput Educ 2020;145:103730.  Back to cited text no. 6
    
7.
Viganò C, Molteni L, Varinelli A, Virzì C, Russo S, Dell'Osso B, et al. Risk of internet addiction in adolescents: A confrontation between traditional teaching and online teaching. Open Psychol J 2020;13:79-85.  Back to cited text no. 7
    
8.
PRAGYATA: Guidelines for Digital Education. Ministry of Human Resource and Development; 2020. Available from: https://www.education.gov.in/sites/upload_files/mhrd/files/pragyata-guidelines_0.pdf. [Last accessed on 2021 Sep 10].  Back to cited text no. 8
    
9.
Engelhardt T. Reading may be harmful to your kids: In the nadirland of today's children's books. Harpers Mag 1991;282:55-62.  Back to cited text no. 9
    
10.
Oxford University Press. Oxford English Dictionary. Oxford, UK: Oxford University Press; 2020.  Back to cited text no. 10
    
11.
World Health Organization. Guidelines on Physical Activity, Sedentary Behaviour and Sleep for Children Under 5 Years of Age. Geneva: World Health Organization; 2019. Available from: https://apps.who.int/iris/bitstream/handle/10665/325147/WHO-NMH-PND-2019.4-eng.pdf. [Last accessed on 2021 Sep 10].  Back to cited text no. 11
    
12.
Radesky J, Christakis D. Media and young minds. Policy statement of the American academy of pediatrics. Pediatrics 2016:138:e20162591.  Back to cited text no. 12
    
13.
Indian Academy of Pediatrics. Screen time Guidelines for Parents. Indian Academy of Pediatrics; 2021. Available from: https://iapindia.org/pdf/Screentime-Guidelines-for-Parents-Ch-005.pdf. [Last accessed on 2021 Sep 10].  Back to cited text no. 13
    
14.
Kaye LK, Orben A, A Ellis D, C Hunter S, Houghton S. The conceptual and methodological mayhem of “screen time”. Int J Environ Res Public Health 2020;17:E3661.  Back to cited text no. 14
    
15.
Przybylski AK, Weinstein N. A large-scale test of the goldilocks hypothesis: Quantifying the relations between digital screen use and the mental well-being of adolescents. Psychol Sci 2017;28:204-15.  Back to cited text no. 15
    
16.
Sanders T, Parker PD, Del Pozo-Cruz B, Noetel M, Lonsdale C. Type of screen time moderates effects on outcomes in 4013 children: Evidence from the longitudinal study of Australian children. Int J Behav Nutr Phys Act 2019;16:117.  Back to cited text no. 16
    
17.
Neuman SB. The displacement effect: Assessing the relation between television viewing and reading performance. Reading Res Q 1988;23:414-40.  Back to cited text no. 17
    




 

Top
 
 
  Search
 
Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
Access Statistics
Email Alert *
Add to My List *
* Registration required (free)

 
  In this article
References

 Article Access Statistics
    Viewed688    
    Printed14    
    Emailed0    
    PDF Downloaded116    
    Comments [Add]    

Recommend this journal


[TAG2]
[TAG3]
[TAG4]