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Prevalence and Determinants of Internet Addiction (IA) and its Association with Psychological Distress and Quality of Life Among Adolescents and Young Adults from a Rural Block of North India
Mohammad Abu Bashar1* and Nazia Begam2
1 Post Graduate Institute of Medical Education and Research, Community Medicine, India
2 ECHS Polyclinic, Naraingarh, India
Submission: February 5, 2020; Published: February 28, 2020
*Corresponding author: Mohammad Abu Bashar, Post Graduate Institute of Medical Education and Research, Community Medicine, Chandigarh, India
How to cite this article:Mohammad Abu Bashar. Prevalence and Determinants of Internet Addiction (IA) and its Association with Psychological Distress and Quality of Life Among Adolescents and Young Adults from a Rural Block of North India. Glob J Addict Rehabil Med. 2020; 6(5): 555696. DOI: 10.19080/GJARM.2020.06.555696.
Introduction
To make communication easier, quicker, and to facilitate safe exchange of information internet was discovered. The use of internet in a healthy manner is defined as achieving a desired goal within an appropriate time period without experiencing intellectual or behavioural discomfort [1]. Over the years, ever increasing use of internet for work and leisure activities has led to its omnipresent presence across all activities of the day and this has disguised the boundaries between functional and dysfunctional internet use. This manifold uses of internet such as establishing risk-free social connections with strangers, free expression of thoughts, possibility to access prohibited content, involvement in unique games, and use of numerous other functions in privacy has led to exponential rise in the use of internet [2-4]. Some individuals cannot control their use of internet, whereas others can limit their use. Internet addiction (IA) can be described as an individual’s inability to control his or her own use of internet causing disturbances and impairment in fulfilment of work, social, and personal commitments [5-7]. Research literature suggests that depression is a leading comorbid disorder with IA [8]. The occurrence of depression among the young individuals with IA and existence of IA among the depressed individuals has been observed. The presence of low self-esteem, low motivation, fear of negative evaluation, social avoidance observed in depressed individuals are hypothesized to lead to excessive/addictive usage of internet in depressed individuals. Social isolation caused by IA may also lead to depressive symptoms. The research evidence suggests that depression can lead to addictive use of internet and vice-versa. Thus, both the mental health conditions have potential to influence and exacerbate each other. With this background, the current study is planned to investigate the prevalence, pattern and severity of IA, and its interrelationship with psychological distress and quality of life among the college going students.
Research Questions
a) What is the prevalence of internet addiction among higher secondary (10+2) students from a semi-urban block of North India?
b) What is the impact of internet addiction on psychological distress and quality of life in these students?
Material and Methods
Study Settings, design and Participants
A Cross sectional observational study would be carried out between October 2018 to December 2018 among higher secondary (10+2) students of two government secondary schools in Naraingarh. Naraingarh is a semi-urban block in district Ambala of Haryana. It is located 55 Kms from Chandigarh, the capital of Haryana. There are approximately 800 students in the higher secondary section (10+2) from three streams i.e. science, arts and commerce. All these students using internet at least for 6-month duration would be included in the study. Consent would be sought from those 18 years of age and Assent would be taken from students less than 18 years.
Study tools
Interview Schedule/Questionnaire: A semi-structured self-administered interview schedule containing information on socio-demographic characteristics of the participants like age, sex, stream of study, total monthly income and socio-economic class and internet usage variables namely duration, frequency, devices used, time spent on internet per day, various purpose for which internet is used, craving for internet use, attempts to reduce internet use, and similar other variables would be used. Family history of substance dependence, personal history of regular use of nicotine, alcohol or other substance and personal history of any other psychiatric disorder etc. would also be recorded in the questionnaire.
Young’s Diagnostic Questionnaire: It is a 20-item selfreported scale based on a 5-point Likert scale to assess the IA and its severity. The scores for the individual items would be summed up for obtaining a total scale which may range from 20 to 100. The total score would be interpreted with the norm criteria of the scale which indicates mild, moderate, or severe categories of IA. According to the criteria, total IAT scores 20-39(mild) represent average users with complete control of their internet use, scores 40-69(moderate) represent over-users with frequent problems caused by their internet use, and scores 70-100(severe) represent internet addicts with significant problems caused by their internet use. This instrument is based on the DSM-IV diagnostic criteria for pathological gambling.
Self-reporting questionnaire: The Self-Reporting Questionnaire (SRQ) is a 20-item self-administered tool developed by the World Health Organization (WHO) specifically for the use in developing countries for screening of mental health conditions at community settings.SRQ-20 offers a yes/no response format to the individual and is designed to identify psychological distress, inclusive of depressive symptoms and suicidality. The SRQ items tap into the diagnostic categories of depressive episodes, dysthymia as defined for instance, in the International Classification of Diseases, 10th Edition (ICD-10). The content validity reportedly for covering psychiatric symptoms inclusive of depressive episodes is high. The SRQ also has acceptable levels of sensitivity (62%–79%) and specificity (62%–75%) for the Indian population of psychiatric inpatients (N = 326).14,15
WHO QOL- BREFF?
This scale is a 26-item instrument for assessing quality of life, which measure the following broad domains: physical health, psychological health, social relationships, and environment. The WHOQOL-BREFF is a shorter version of the original instrument that may be more convenient for use in large research studies or clinical trials.
Procedure
The study would be conducted after obtaining the approval from the Institutional Ethical Committee (IEC) and the permission from the school authorities of the two schools. The study investigators would visit the college and the semi-structured proforma along with the scales would be distributed in classes, each with roughly 40 students after giving the necessary instructions. All the eligible students giving consent/assent would be included.
Statistical Analysis
All the study data were analysed using IBM SPSS Version 22.0 for Windows. Measures of central tendency and Spearman’s rank correlation would be used to assess the relationship between the IA and SRQ scores and between the IA and QOL score. Mann- Whitney U test and Kruskal- Wallis tests would be utilized to detect the difference among groups. Logistic Regression analysis would be carried out to identify the predictors of IA. Age, gender, SRQ score, QOL-BREFF score, duration of internet use, average time spent on internet, and frequency of internet use would be the factors which would be entered in the regression equation for conducting the logistic regression analysis. The significance value for the study results would be set at P<0.05.
References
- Davis RA, Flett GL, Besser (2002) Validation of a new scale for Measuring Problematic Internet use: Implications for pre-employment screening. Cyberpsychol Behav5(4): 331-345.
- Livingstone SM, Sonia Livingstone (2002) Social Shaping and Consequences of ICTs.
- Teo TS, Lim VK (2000) Gender differences in internet usage and task preferences. Behav Inform Techn 19(4): 283-295.
- Young KS Internet addiction: Symptoms, evaluation and treatment. In: VandeCreek
- L Jackson T (2018) Innovations in Clinical Practice: A Source Book 17: 19-31.
- Young KS (1999) Internet addiction: Symptoms, evaluation and treatment 17: 19-31.
- Young KS (2004) Internet addiction: A new clinical phenomenon and its consequences. Am Behav Sci 48(4): 402-415.
- Stanton JM (2002) Company profile of the frequent internet user. Communications of the ACM 45(1): 55.
