|Year : 2021 | Volume
| Issue : 2 | Page : 90-94
The association between depression or stress and internet addiction
Akash Vishwakarma, Manoj Kumar Sharma
Department of Clinical Psychology and Service for Healthy Use of Technology Clinic, National Institute of Mental Health and Neuro Sciences, Bengaluru, Karnataka, India
|Date of Submission||07-Nov-2020|
|Date of Decision||21-Feb-2021|
|Date of Acceptance||22-Feb-2021|
|Date of Web Publication||22-Jun-2021|
M. Phil Akash Vishwakarma
Department of Clinical Psychology, National Institute of Mental Health and Neuro Sciences, Bengaluru -560 029, Karnataka
Source of Support: None, Conflict of Interest: None
Objective: In the current study, we intended to examine the association between affective states (depression, stress, and anxiety) and Internet addiction (IA). Methods: The study sample consisted of 291 individuals with the age of 18–40 years. We used an online survey on study participants with the IA Scale (20 items) and the Depression Anxiety Stress Scale-21. Results: The mean age ± standard deviation of the sample was 23.58 ± 4.40 years. The results of stepwise regression analysis indicated that depression (p < 0.001) and stress (p < 0.01) significantly contributed to IA. Anxiety did not significantly contribute to IA. Conclusion: This study showed that depression and stress were related to Internet use. This finding implies the need for early identifying depression and stress for giving an appropriate intervention for the individuals with IA.
Keywords: anxiety, Depression Anxiety Stress Scale-21, Internet addiction test, stepwise regression analysis
|How to cite this article:|
Vishwakarma A, Sharma MK. The association between depression or stress and internet addiction. Taiwan J Psychiatry 2021;35:90-4
|How to cite this URL:|
Vishwakarma A, Sharma MK. The association between depression or stress and internet addiction. Taiwan J Psychiatry [serial online] 2021 [cited 2021 Oct 22];35:90-4. Available from: http://www.e-tjp.org/text.asp?2021/35/2/90/318963
| Introduction|| |
Internet use has become the platform for enhancing connectivity and productivity, but the concerns have also been expressed for its negative consequences like addiction. Internet addiction (IA) implicates an individuals' inability to control their use of the Internet, which eventually causes marked distress and/or functional impairment ,,. India is the second-largest online market in the world in 2021; on an estimate, there will be around 635.8 million Internet users. In 2015, around 26% of the Indian population used the Internet, which indicates a remarkable increase compared with the preceding years. In gender, men (71%) have higher Internet use when compared to women (29%) in India . McKinsey Digital India report in March 2019 revealed that India had 560 million Internet subscribers in 2018 . A media report published on January 30, 2020, showed that India has crossed the 500 million mark at the end of 2019 for the number of smartphone users . There are 8.5% of Internet users in India. Mumbai, having 3.24 million users, holds first place, and Delhi, having 2.66 million users, holds second place in the number of Internet users in the age group of 16–45 years . In the United States, 87% of teenagers in the age group of 12–17 years used the Internet compared to 73% in 2000 and 66% of Internet users in other Western and European countries .
The prevalence of psychological morbidities is seen among treatment seekers for IA. A Korean study of 1,573 high school adolescents was found to have 1.6% severe IA and that 38.0% of them are classified as possible Internet addicts. They also found that depression and suicidal ideation are highest in the Internet-addict group in comparison with non-Internet addict group . Another meta-analysis showed that IA is associated with alcohol abuse, attention deficit and hyperactivity, depression, as well as anxiety . Depressive disorder has been found to be associated with IA in the population . Youths experiencing depression are progressively inclined to invest more energy in the web , and the other way around, those associated with over-the-top use of the Internet are bound to be depressed ,,. People with IA have shown their anxiety with various modes of operation such as checking e-mails at midnight after suddenly waking from sleep or connecting to the Internet first thing in the morning. The perceived detachment from reality, inadequate sleep, and persistent anxiety of not being online for hours, social isolation, and occupational dysfunction all lead the individual to experience extreme depression . A positive correlation exists between the level of anxiety and IA ,. People addicted to alcohol, cigarettes, drugs, food, and/or sex have a higher risk of developing IA because they have learned to deal with anxiety and difficulties through compulsive behavior . In this study, we intended to comprehensively study the association between affective states (anxiety, stress, and depression) and IA.
| Methods|| |
A total of 313 participants expressed a willingness to participate in the web-based survey. Among them, 291 participants who had completed survey protocols were used for the study. In this online survey, the participant's age range was 18–40 years, with 23.58 ± 4.40 (mean age ± standard deviation) years. The web-based questionnaire to assess Internet and affective state was distributed on Facebook, WhatsApp, and other platforms to obtain the most heterogeneous sample possible. The affective state refers to the experience of feeling the underlying emotional state. In the present study, we assessed broadly three affective states, i.e., depression, anxiety, and stress. The survey period had lasted for six weeks. Participants gave their informed consent by checking the acceptance (yes) of the question for participating in the study and allowing a researcher to use the data for the research purpose. Incomplete participates' protocols were excluded for understanding the association between affective states and Internet uses. Exclusion criteria were those who were out of the age range for the study. This study was approved by the Institute Ethics Committee (protocol number = NIMHANS/3RD IEC [BEH.SC.DIV]/2016, date of approval = December 27, 2016, and approval number = 2232). The patients also needed to give their consent to participate in the study.
Age, gender, education qualification, family type, having an active Internet connection, and daily Internet uses were assessed. We also collected information about continuous desire to use the Internet, having a lack of control over the use of the Internet, and denial of the bad effect of the Internet.
Depression Anxiety Stress Scale
Depression Anxiety Stress Scale-21  is a 21-item self-report questionnaire designed to measure the frequency and severity of symptoms of depression, anxiety, and stress over the previous week. The severity ratings are based on a four-point Likert scale which has options ranging from zero (not applying to me at all) to three (applying to me very much).
Internet addiction test
Internet addiction test (IAT)  is a 20-item questionnaire on which respondents have to rate the item on a five-point Likert scale, covering the degree to which their Internet use affects their daily routine, social life, productivity, sleeping pattern, and feeling. A higher score indicates of the high level of Internet use. Young in 2011  suggested that total scores ranging from 0 to 30 points are considered to reflect a normal level of Internet usage, scores of 31–49 indicate the presence of a mild level of IA, scores of 50–79 reflect the presence of a moderate level, and scores of 80–100 indicate a severe dependence on the Internet.
Data were collected through a Google Forms survey. Invitations by E-mail, WhatsApp, and Facebook messengers were sent out to all the participants. The copies of questionnaire with all the instructions provided a link to the survey. The survey also provided an option for participants to invite their friends to participate in the study. Consent was taken from the participants at the time of filling the form. The item for consent was: “I understand that, my participation is completely voluntary. I will need to provide my contact information so that I can be sent the future survey to answer, however, my contact information will not be passed to any third parties and will be removed from my answers before any analysis takes place. The data gathered in the study will be stored securely and it will not be possible to identify me.” Confidentiality and anonymity about the survey responses were assured for all the participants.
We used descriptive statistical analysis for all the nominal and ordinal data. A Chi-square test was used to test categorical variables. Stepwise regression analysis was used to find the significant predictors of depression, anxiety, and stress for IA. IA was taken as a dependent variable while depression, anxiety, and stress as a predictor variable or independent variable. We checked linearity by analysis of variance (ANOVA).
We used the Statistical Package for the Social Science version 20.0 for Windows (SPSS International Business Machines Corp, Armonk, NY, USA) to compute the study data. The differences between groups were considered significant if p < 0.05.
| Results|| |
The mean age ± standard deviation of the sample was 23.58 ± 4.40 years [Table 1]. [Table 2] shows significant differences for an association between depression (p < 0.001), stress (p < 0.001), or anxiety (p < 0.001) and IA. The results of stepwise regression analysis [Table 3] showed that depression (p < 0.001) and stress (p < 0.01) were significantly contributed to an Internet use disorder. But [Table 3] shows that anxiety was not significantly contributed to an Internet use disorder.
|Table 2: Distribution of depression, anxiety, stress, and Internet use scores among participants|
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|Table 3: Affective state and Internet addiction (dependent variable is Internet use)|
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The linearity checked based on ANOVA output [Table 4]; the significant value found to be smaller than 0.001, implying absence of the linear relationship among the variables of IA, depression, and stress.
| Discussion|| |
The study documented the depression and stress with IA among participants with a mean age of 23.58 ± 4.40 years. 12.3% of the users got above a moderate level of addiction. A similar trend has been observed in the other study done among 596 college students from South India. Results indicated that among the sample, 246 (41.3%) were mildly addicted and 91 (15.2%) were moderately Internet addicted . In an Indian Council of Medical Research-funded survey of behavioral addiction, among 2,755 people from Bengaluru aged 18 to 65 years, addiction found for behaviors which include 4.1% of mobile phones, 3.5% of social networking sites, 4% of online shopping, 2% of online pornography, and 1.2% of gambling . Other studies from urban areas of Indian documented a percentage of 24%–34% for mild IA level and 7%–24% for a moderate level of dependence ,,.
A significant difference with a p-value for affective states and Internet use was shown in [Table 3] and [Table 4]. A total of 987 students from Mumbai have been cross-sectionally assessed using IAT  and Duke Health Profile . Using Young's original criteria, the users were divided into groups: 74.5% as moderate users, 24.8% as possible addicts, and 0.7% as addicts. The study result was found that Internet addicts have high anxiety and depression . Another study from India conducted in North Indian universities showed that depression, anxiety, and stress are independent predictors of IA . Research done among middle school students in China was found that adolescents from different social classes have different types of anxiety symptoms when they feel stressed, which influences their choices concerning Internet use, indicating the presence of an affective state predicting the use of Internet use .
Findings in our study demonstrated that affective states predicted increased Internet uses among the participants. As shown in [Table 3], depression (p < 0.001) and stress (p < 0.01) were significantly predicted IA positively. Another study was done to evaluate the relationship between IA and anxiety. Among 392 students from Afyon Kocatepe University, Turkey, higher Internet-addictive groups have a high score on the Beck Anxiety Inventory. In the hierarchical linear regression analysis, the avoidance domain of social anxiety was the strongest predictor of the severity of IA . Ren et al. found that social anxiety and loneliness increase the likelihood of IA among middle school students . Recent studies have shown a positive association among depression, anxiety, and IA ,,,,. The available research literature indicates that depression and anxiety are associated with IA.
The present understanding of the underlying psychological variable can be beneficial in formulating early identification, assessment, and intervention strategies for both affective states and IA as either of these conditions can be a risk factor of the emergence of the others.
The readers are cautioned not to overinterpret the study results because this study has four major limitations:
- We could not evaluate another factor including personality and assess the off-line relationship.
- Since the study was carried in the metropolitan city of India, it did not speak to web users across the educational level.
- It is altogether possible that individuals were one-sided while reacting to the examination's inquiries. They may have offered socially attractive and mixed-up responses.
- We had an overwhelmingly female example in this study. Therefore, our results cannot extrapolate to different populations and long-term effects without any additional assessment.
The result from the current study showed the association of depression and stress with IA, and this association was also seen in other studies. Hence, the study implies a large sample size study to consolidate with equal representation of gender and wider age group. These findings also imply integrating these affective components in the planning management module to manage online activities.
| Acknowledgment|| |
The authors thank for the cooperation of all the study participants.
| Financial Support and Sponsorship|| |
This research was not funded by any institution.
| Conflicts of Interest|| |
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[Table 1], [Table 2], [Table 3], [Table 4]