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SHORT COMMUNICATION
Year : 2022  |  Volume : 31  |  Issue : 2  |  Page : 359-363  Table of Contents     

Affective symptoms as a predictor of internet addiction among young adults


1 Department of Clinical Psychology, National Institute of Mental Health and Neuro Sciences (NIMHANS), Institute of National Importance (INI), Bengaluru, Karnataka, India
2 Department of Biostatistics, National Institute of Mental Health and Neuro Sciences (NIMHANS), Institute of National Importance (INI), Bengaluru, Karnataka, India
3 Department of Neurochemistry, National Institute of Mental Health and Neuro Sciences (NIMHANS), Institute of National Importance (INI), Bengaluru, Karnataka, India

Date of Submission06-Aug-2021
Date of Acceptance25-Feb-2022
Date of Web Publication30-Aug-2022

Correspondence Address:
Dr. Manoj K Sharma
SHUT Clinic (Service for Healthy Use of Technology), NIMHANS Centre for Well Being, National Institute of Mental Health and Neuro Sciences (NIMHANS), Bengaluru, Karnataka
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/ipj.ipj_175_21

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   Abstract 


Objectives: Mental health difficulties have been found to be associated with internet addiction, which makes it a multifaceted problem. The current study aimed to examine the relationship between internet addiction and affective states (depression, anxiety, and stress). Material and Methods: The study sample consisted of 731 individuals (403 males and 328 females) ranging in age from 18 to 25 years. We used an observational survey design to study participants with an internet addiction test and depression, anxiety, and stress scale. Results: The mean age ± standard deviation of the sample was 22.58 ± 2.80 years. Stress and depression were found to play a major role in internet addiction in the regression analysis. Conclusions: The study supports the association between internet use and stress and depression. The findings imply the need for early identification and intervention of affective states in the context of unhealthy internet use.

Keywords: Anxiety, depression, internet addiction, stress


How to cite this article:
Anand N, Sharma MK, Marimuthu P, Huchegowda R, Thakur PC, Vishwakarma A, Tadpatrikar A, Mondal I, Azhagannan KM, Rawat VS. Affective symptoms as a predictor of internet addiction among young adults. Ind Psychiatry J 2022;31:359-63

How to cite this URL:
Anand N, Sharma MK, Marimuthu P, Huchegowda R, Thakur PC, Vishwakarma A, Tadpatrikar A, Mondal I, Azhagannan KM, Rawat VS. Affective symptoms as a predictor of internet addiction among young adults. Ind Psychiatry J [serial online] 2022 [cited 2022 Dec 2];31:359-63. Available from: https://www.industrialpsychiatry.org/text.asp?2022/31/2/359/355056



Internet addiction (IA) refers to symptoms resulting from indulgence in excessive online activities.[1] Internet use is additionally conceptualized as a coping response to psychosocial stressors like occupational stress, loneliness, and boredom. Online activities, when used excessively to cope with current negative mood states (e.g. stress, depression, and anxiety), leads to less use of alternate healthy coping behaviors (e.g. talking to others, engaging in social or physical activity/sports). Internet use may then be used as a means of avoiding negative feelings, possibly leading to excessive or problematic internet use.[2] Individuals with a maladaptive coping style (i.e., avoidance) and those who expect to use the internet to modify their mood, may be more likely to develop IA.[3]

Excessive internet users are more likely to use avoidance and emotion-focused coping responses than healthy users of the internet, and they are less likely to use adaptive problem-focused coping responses. Research findings indicate strong positive correlations between IA and avoidance coping among college students.[4] In a cross-sectional evaluation among university students (n = 2776), those who were male stayed in rented accommodation, spent more than 3 h per day on internet use, and had depressive symptoms were more likely to have IA.[5] Similar findings of IA being predicted by the presence of depressive symptoms have been reported among students studying engineering (n = 1086)[6] and medicine (n = 1763) as well.[7] In another study, there was a significant association between IA and stress, depression, and anxiety among 440 adolescents. The majority (73.1%) of the respondents were females (mean age, 17.21 years).[8] IA was also shown to be associated with the presence of higher levels of depressive symptoms, perceived stress, and burnout among 376 medical professionals in the age group of 24 to 39 years.[9]

In another study, using a longitudinal design with 699 adolescents (age range 13–17 years), depressive symptoms at time point 1 predicted an increase in excessive internet use (online social relationships, online use for mood regulation) and negative outcomes at time point 2 (after 1 year).[10] In turn, negative outcomes at time point 1 predicted an increase in depressive symptoms at time point 2. Another longitudinal study (n = 660) conducted with adolescents aged 12 to 15 years in the Netherlands found social media use resulted in excessive use of the internet and depression 6 months later.[11] Yet another study, among Chinese adolescents (n = 8286), indicated bidirectional associations wherein depression status at baseline significantly predicted the new incidence of IA at 12-month follow-up and vice-versa (baseline IA status also significantly predicted the new incidence of probable depression).[12] With the existing literature, it remains unclear whether the relationship between IA and depression is unidirectional or bidirectional.

The current study investigated not only the relationship between affective states (depression, anxiety, and stress) and excessive internet use but also evaluated the role of affective states in predicting internet addiction.


   Material and Methods Top


Participants

A total of 731 individuals (403 males and 328 females) with an age range of 18 to 25 years, were approached using the observational survey design for the administration of study tools. It included participants using the internet/smartphones for a minimum period of one year or more. Exclusion criteria were those who were out of the age range for the study. The study was approved by the Institute Ethics. The participants were also required to give their consent to participate in the study

Measures

Sociodemographic data

Age, gender, education qualification, family type, having an active Internet connection, and daily Internet uses were assessed. We also collected information regarding the pattern and impact of internet use.

Internet addiction test (IAT)

The IAT measures the characteristics and behaviors associated with compulsive use of the internet, including compulsivity, escapism, and dependency. It is a 20-item self-report scale using a 5-point Likert scale to assess the IA and its severity.[13]

Depression anxiety stress scales (DASS-21)

The DASS-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 DASS-21 scales have high internal consistency in this population. The ratings of severity are given on a 4-point Likert scale from 0 = did not apply to me at all to 3 = applied to me very much.[14]

Procedure

The administration of tools was carried out after obtaining their informed consent in an individual setting. In all, 731 individuals (403 males and 328 females) in the age group of 18 to 25 years participated in the study. All the participants were assured of confidentiality and anonymity regarding the survey responses.

Statistical analysis

We used descriptive statistical analysis to assess all the nominal and ordinal data. A Chi-square test was used for categorical variables. The 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 were taken as predictor variables or independent variables. We checked linearity by analysis of variance (ANOVA). We used the Statistical Package for 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 < 0.001


   Results Top


There were 731 individuals (403 males and 328 females) in the age group of 18 to 25 years. The mean age ± standard deviation of the sample was 22.58 ± 2.80 years. The usage pattern of internet users did not differ in terms of gender. About 40.7% (n = 298) got a score above a moderate level of internet addiction.

[Table 1] indicated that affective states were significantly associated with the category of internet use pattern.
Table 1: Relationship of affective states and internet use pattern

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[Table 2] shows that stress, anxiety, and depression were significantly associated with higher internet use. Mean values were higher for depression and stress in comparison to anxiety.
Table 2: Distributions Internet use scores and Stress, Anxiety and Depression

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[Table 3] shows that higher levels of internet addiction were associated with higher levels of stress and depression. Linearity was checked by ANOVA and the R2 was 0.49, indicating that these two variables (stress and depression) explain 49% of the variability of internet addiction. The regression analysis indicates that stress and depression were independently associated with internet addiction, with more shared variance with stress than with depression. Anxiety did not share a unique variance with internet addiction.
Table 3: Internet addiction test and Affective states (Dependent variable is Internet use)

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   Discussion Top


In this study, we tried to explore the relationship between internet addiction and the affective states of depression, anxiety, and stress. An observational survey design comprising the internet addiction test and depression, anxiety, and stress scale was used to study 731 individuals for this purpose. The participants in the study had a mean age of 22.58 ± 2.80 years and were found to have stress and depression as a result of their IA. It was found that the majority of users (40.7%) had a moderate level of internet addiction. The results indicated that affective states were significantly associated with internet use, wherein a higher level of stress and depression predicted internet addiction. According to the theory of compensatory internet use, negative life situations such as stress and depression can give rise to a motivation to go online to alleviate negative feelings.[15] These results also support the hypothesis from the cognitive behavioral perspective that the presence of previous psychological distress could be a factor that will increase the risk of danger for the development of problematic or excessive internet use.[16],[17],[18]

Stress has been documented in the literature to be closely related to internet addiction. Stress is a part of every individual's life that requires some kind of definite response to any taxing change or demand. Stress at times takes an emotional toll, and to relieve themselves from the negative feelings, people turn to certain activities that can make them feel better. According to the Cognitive Phenomenological-Transactional theory, the manner used to resolve stress and the way people react to stressful situations play an intermediate role in developing internet addiction. For example, individual coping styles, time management tendencies, and having problematic personal traits such as risk-taking behavior, and impulsiveness can give rise to excessive internet use.[19] These results can be corroborated with other study findings which also indicate the existence of a relationship between stress and the addictive use of the internet.[20],[21]

The results also showed a strong correlation between internet use and affective states, especially depression. Many studies have found a reciprocal relationship between internet use and depression. One possibility is that depressed people have fewer social skills, are less attractive to peers, and making them more likely to be isolated in real life. In order to relieve themselves from the negative feelings associated with depression, their internet dependency has increased. Often, there is a vicious cycle of depression that results in internet addiction, which further increases depression because using the internet makes one aware of personal and social skills deficiencies.[21],[22]

In the background of available studies about the unidirectional or bidirectional relationship between internet addiction and affective states,[12] this research study also highlights the importance of the need for early identification and intervention for both psychological problems and excessive internet use. Although the causal direction could not be determined, it is plausible that either of these conditions could be a risk factor for the emergence of the other. The current understanding of the underlying psychological variables can be used to develop early detection and intervention strategies for both affective states and internet use.

Limitations of the study include a lack of measurement of social desirability for reporting the severity of internet use. In addition, the presence of depression and anxiety may affect the reporting of the severity of internet use. In the future, the effects and mechanisms of IA could be further explored through qualitative interviews and studies involving longitudinal designs.


   Conclusions Top


The results from the current study showed the association of depression and stress with IA, and more variance in IA was due to stress. This association was also seen in other studies. These findings also imply addressing these affective components in the planning intervention module to manage online activities.

Financial support and sponsorship

Rajiv Gandhi National Institute of Youth Development, Sriperumbudur, Chennai, India.

Conflicts of interest

There are no conflicts of interest..



 
   References Top

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