A study of prevalance of internet addiction and its association with depression and anxiety among medical students

Introduction: With the advent of technology, medical education has been transformed to the extent that internet has become a necessary part of it. The use of Internet ranges from purely academic purposes like acquisition of knowledge and research to completely leisure activities. While proper use of internet has its own benefits, problematic internet use can disrupt occupational and social life. It has been reported to be allied with anxiety disorders, introversion, pathological gambling, personality disorders, bipolar disorder and depression in young people. DSM-V classifies Internet Gaming Disorder in Section III and in the beta draft of ICD-11 it is included as a diagnosis under disorders due to addictive behaviours (6C51). Aim: To study the prevalence of internet addiction and its association with Depression and Anxiety among Medical Students. Materials and Methods: Cross sectional study involving 700 medical students who were using internet for more than 6 months duration was conducted. A pretested self-reported questionnaire, Young’s Internet Addiction Test, Beck’s Anxiety Inventory and Beck’s Depression scale were administered. Statistical analysis was done using latest IBM SPSS 2.0 Software. Results: Majority of the students 51.8 % belonged to 21-25 years age group. The prevalence of Internet Addiction was found out to be 19.1% with moderate addiction of 17.4%, and severe addiction of 1.7%. Among the internet addicts, 58.9% reported anxiety symptoms and 32.8% scored high on Becks Depression Scale. Conclusion: Around 1/5 of our sample had internet addiction which had positive correlation with Depression & Anxiety, indicating need for preventive measures like proper education, support groups and physical activities etc.


Introduction
With the advent of technology, medical education has been transformed to the extent that internet has become a necessary part of it. Internet can be used in various ways like to gain information, communication and for scientific research. It can also be used for gaming, pornography and gambling. Problematic internet use can disrupt occupational and social life. 1 As per Shaw M and Black DW, IA can be described as "excessive or poorly controlled preoccupations, urges, or behaviors regarding computer use and Internet access that lead to impairment or distress". 2 Internet Gaming Disorder is classified under Section III of DSM-V, which conceptualizes it as persistent and recurrent use of internet for gaming with increased preoccupations, withdrawal symptoms, tolerance, unsuccessful attempts to control the use, continued use despite knowledge of harm in a 12 month period which is in line with criteria's for substance use disorder. 3 Furthermore, In the beta draft of ICD-11 it is included as a diagnosis under disorders due to addictive behaviours (6C51). 4 Gaming disorder is characterised by i) impaired control over gaming ii) Increasing priority to gaming over other activities and iii) continuation of gaming despite of negative consequences.
Thus, IA is thought to be a psychiatric disorder with precise diagnostic and management principles. Jerald Block, a psychiatrist from US conceptualized IA as a "compulsiveimpulsive spectrum disorder" and argued that the definition should include both online or offline computer usage and conceptualized that excessive gaming, sexual preoccupations, and email/text messaging are three subtypes of IA. 5 Young individuals with internet addiction can develop various mental health problems due to excess time spent on online shopping, gaming, chatting, pornographic sites and hobby sites. Internet addiction is also associated with anxiety disorders 6 , personality disorders, bipolar disorder, social phobia and depression and other mental health problems such as pathological gambling, game playing, especially in young individuals. 7 Depression and Internet addiction are associated with each other. Depressed individuals have low self-esteem, feel lonely, have high need for affiliation all of which can lead to excess use of internet. 8 On the other hand individuals with excess internet use are usually socially isolated which can lead to depression. 9 Internet Addiction can lead to anxiety and stress. 10 Individuals suffering from anxiety and stress face difficulties in developing meaningful communications in real world which can lead to more use of social media sites.
Many studies describe the prevalence of internet addiction among university students in other countries, however only a few studies are there from Indian subcontinent. Studies from Indian subcontinent are mostly from large metro cities and there is lack of data from smaller cities. Lesser facts are available on the association between internet addiction and mental health problems like depression and anxiety specifically among medical students.
Hence through this cross sectional study we describe the prevalence of internet addiction and its association with depression and anxiety among medical students of Kalaburagi district of Karnataka, India.
Aims and Objectives 1. To study prevalence of internet addiction among medical students. 2. To study association between Internet Addiction and Anxiety symptoms. 3. To study association between Internet Addiction and Depressive symptoms.

Materials and Methods
We conducted a cross sectional study among medical students of Kalaburagi with approval from Ethics Committee of the institute from 1 st May 2018 to 15 th July 2018. Three medical colleges in Kalaburagi district were approached and their students were included for the study. A simple random sampling method was used for recruitment. Consent from all students was obtained. The students were informed about the subject and purpose of the study and 4 page questionnaire was filled under guided supervision. The procedure took approximately 30 minutes.
In total 730 students participated in the study, out of which 700 had given completely filled forms. Thus the population of study considered was n=700.

Sampling technique
Simple random sampling method

Inclusion criteria
Medical students from all the four professional years, using internet since at least last six months, who gave written consent were included for the study.

Exclusion criteria
Students who were absent on the day of study. choice self-report inventory with each answer being scored on a scale value of 0 (not at all) to 3 (severely). Total score range from 0 to 63. 14 0-7 normal/ minimal anxiety, 08-15 mild anxiety, 16-25 moderate anxiety and 26-63 severe anxiety.

Statistical analysis
All the data was entered and tabulated using SPSS version 20.0 software. Descriptive statistics were calculated. Chi square test and Pearson correlation test was applied and P value was calculated. The significance obtained was of p<0.05 which means variables are strongly correlated with each other.

Results
Of the 700 students comprising the study group, 372 (53.14%) were females and 328 (46.8%) were males. Majority of the participants 51.8 % belonged to 21-25 years age group followed by less than ≤20 years i.e. 42.6%.  The reason for internet use was reported as Entertainment by majority 81 % of students. 36.1% used internet for academics, 35% involved themselves in social friendships online whereas 11.4 % reported their loneliness as the reason. 51% kept their phone next to bed while sleeping at night and 50.6% checked their phone on getting up in the morning even before brushing their teeth/going for toilet.

Association of internet addiction with anxiety
Out of 700 students 191 (27.2%) reported anxiety symptoms. Whereas out of total 134 internet addicts 79 (58.9%) students had anxiety symptoms. Study reveals that, there was statistically very high significant association between internet addiction and anxiety (P<0.001). Out of 238 students who used internet for >4 hours daily, 78 (32.8%) students had anxiety symptoms as compared to 194 students who used internet for 0-2 hours daily among them 43 (22.1%) students reported anxiety symptoms. As the number of hours spent online increased, the anxiety symptoms also increased which showed statistically very high significance.  Out of 700 students, 304 (43.5%) stayed on line permanently, among them 110 (36.2%) developed anxiety symptoms. Whereas out of 396 students logging on occasionally, 81 (20.4%) reported anxiety symptoms. Students who permanently logged on vario us social media sites developed anxiety symptoms more than those occasionally logged on which was statistically significant. The students who used > 4 GB were 9, and among them 4 students (44.4%) reported anxiety symptoms. Whereas 200 students who used 1-2 GB data/day among them 69 (34.5%) reported anxiety symptoms. Thus as the amount of data used increased, the anxiety symptoms also increased which was statistically significant. 357 (51%) students kept phones next to bed while sleeping at night and they checked phones repeatedly, among them 110 (30.8%) reported anxiety symptoms. Similarly 354 (50.6%) students checked their phones as soon as they got up from bed, among them 117 (33%) reported anxiety symptoms. Thus more Anxiety symptoms were noticed in those who kept their phones next to bed while sleeping and checked their phone immediately when they got up in the morning which was statistically significant.

Association of internet addiction with depression
Out of 700 students, 97 (i.e. 13.8%) reported depressive symptoms. Out of 700 students, 134 were internet addicts and among them 44 (32.8%) reported depressive symptoms. As the severity of internet addiction increased, higher depressive symptoms were noted. In our study, very high statistical significant association is seen between internet addiction and Depression (P<0.001). Out of 700 students, 194 (27.7%) used internet for 0-2 hours/day and among them 13 (6.7%) reported depressive symptoms. Whereas 238 students assessed internet for more than 4 hours daily and among them 50 (21%) reported depressive symptoms. Thus the students who spent more hours online reported more depressive symptoms which was statistically highly significant. were from nuclear and 4 from divided family and 11 from Joint family. Thus Depressive symptoms were seen more in students from Nuclear than joint families which was statistically significant. Out of 700 students, 449 were using up to 1 GB of data, among these 46 (10.2%) reported depressive symptoms. Whereas 51 used more than 2 GB data and 11 (21.7%) were found to have depressive symptoms. Thus students who were using >2 GB of data daily were found to have more co morbid Depressive Symptoms which was statistically significant.

Fig. 3: Number of students with without depressive symptoms and its association with login status
Out of 700 students, 80 students reported Loneliness to be their reason to use excessive internet. Among them 27 (33.8%) were found to have depressive symptoms which was statistically significant when compared to others reasons to internet access. (  =13.69 P<0.01).

Fig. 4: Loneliness & association with depression
Out of 700 students, 357 (51%) kept phones next to bed while sleeping at night, among them 62 (17.4%) reported depressive symptoms. Similarly, out of 700 students, 354 (50.6%) checked their phones as soon as they got up from bed, among them 62 (17.5%) reported depressive symptoms. Thus more Depressive symptoms were noticed in those who kept their phones next to bed while sleeping and checked their phone immediately when they got up in the morning which was statistically significant. (P<0.01)   18 The level of internet addiction differs from one study to another. These discrepancies can be explained by the differences in methods used for the diagnosis of internet addiction and differences in study populations. In our study group, IA, anxiety and depression was higher among students from Nuclear and Divided families than Joint families. It is well known that although individuals may have "real social support" from their families and society, they may also have "virtual social support" from the internet. 19 Individuals separated from their families, use the internet frequently to satisfy their need for interpersonal relationships and to create alternative social channels.
In diagnosing Internet Addiction, time spent on the internet is one of the important factors. A use of 40-80 hours weekly or up to 20 hours at one time can serve as an indication for hospitalization. 20 In our study, students who used the internet 4 or more hours daily, 30 hours/week scored high on IA, Anxiety symptoms and depressive symptoms (p<0.05) As rightly pointed by Young (2004) cases of problematic internet use should be screened for depressive symptoms. In our study, depression and internet addiction had significant positive correlation (p<0.05). There were 44 (32.8%) who had depressive symptoms of all 134 internet addicts which is in accordance with Indian study by Subhashini J where 38.7% of internet addicts reported depression. 21 Also various other recent studies have shown that Internet Addiction causes decrease in social interactions, depression and loneliness and lower selfesteem. 22 In our study 27 (33.8%) students who scored high on Depressive symptoms had reported loneliness as frequent reason for use of internet which is in consistence with other studies done in the past which showed positive correlation between IA and Depression.
There is lack of research depicting relationship between IA and Anxiety symptoms. Excessive internet use is associated with loneliness, decreased self-esteem, lower satisfaction levels in life, anxiety symptoms and overall poor mental health. Consistent with this, anxiety and IA was seen positively correlated in our study. Out of total 134 internet addicts 79 (58.9%) students had anxiety symptoms.
We also noted that the students who kept their phone bed side while sleeping at night and first thing they did was to check their phone in the morning, scored high on IA, anxiety symptoms and depressive symptoms as they had repeated urge to check their phones so as not to miss any of the notifications.

Conclusion
The present study revealed that of all 700 students 80.9% were normal internet users, 19.1% were IA among them 17.3% had moderate IA and 1.8% had severe addiction. IA is seen to be positively correlated with Depressive and anxiety symptoms. The cause-effect relationship between depression and IA is not clear, nevertheless it is beneficial to screen for depression in individuals with IA. Various factors like stressful educational process, uncertainty of living away from one's family, financial and emotional stress may lead to depression or internet addiction among students. Hence, treating the underlying depressive symptoms may help to decrease internet addiction. Appropriate preventive strategies like educating students about healthy use of internet, stress management techniques, coping strategies, maintaining good peer relationships, importance of offline world need to be taught in order to protect the physical and mental health of the users. Parents and teachers need to be sensitized regarding identification of problematic internet use and further referral to advanced centers for screening and management.
Acknowledgement I extend my gratitude to all the participants for their whole hearted co-operation, without whom the study would not have been possible. I extend my gratitude and thanks to the Dean, the Director and Head of Departments of MR Medical College for supporting me and being an anchor for the whole study. I am thankful to my students Dr. Dilpreet Kaur Jattana, Dr. Abdul Rafe Muqtadeer Baig and Miss Vani Vijra for helping me to plan and implement my work.

Limitations of the study
The study design being cross-sectional could not conclude a cause-effect relationship between the causative factors and IA. As the study involved only medical students from a district of Karnataka with a small sample size; therefore findings cannot be generalized to the community. The tools used were self-reported questionnaires which could have led to errors in the study results. No control group was included in the study.

Conflicts of interest
There is no conflict of interest.