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 Table of Contents  
Year : 2021  |  Volume : 4  |  Issue : 1  |  Page : 30-35

A study of correlates of social networking site addiction among the undergraduate health professionals

1 Department of Psychiatry, Dr. M. K. Shah Medical College and Research Center, Ahmedabad, Gujarat, India
2 Department of Psychiatry, GMERS Medical College Sola, Ahmedabad, Gujarat, India
3 Department of Psychiatry, M. P. Shah Medical College, Jamnagar, Gujarat, India

Date of Submission14-Nov-2020
Date of Decision02-Jan-2021
Date of Acceptance13-Jan-2021
Date of Web Publication9-Feb-2021

Correspondence Address:
Parveen Kumar
2nd Floor Trauma Building, Department of Psychiatry, M.P. Shah Medical College & G. G. Hospital, Jamnagar 361 008, Gujarat
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/shb.shb_1_21

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Introduction: Social networking sites (SNSs) are popular, and there is a concern regarding its addiction among the young adults. The present study aimed to find the correlates of SNS addiction among the undergraduate health professionals. Methods: This was a 6-month, cross-sectional, and observational study of 730 undergraduate health professionals of government medical, dental, and physiotherapy colleges of Jamnagar, Gujarat, India. Participants were selected using stratified random sampling from the medical, dental, and physiotherapy government colleges. The Social Media Disorder Scale was used to detect the SNS addiction, the Fear of Missing Out (FOMO) Scale was used to find the severity of FOMO, the Perceived Stress Scale was used to detect the severity of stress, and the Insomnia Severity Index was used to detect the severity of insomnia in health professionals. Descriptive statistics, Chi-square test, and multiple regression analysis were used for analysis of data. Results: The prevalence rate of SNS addiction was 15.02% among the undergraduate health professionals. Participants with addiction were using SNS widely (hostel, home, college, and leisure hours), spent more time and money on Internet, started SNS use before 5 years, and reported FOMO. They also reported moderate-to-severe stress and insomnia. Conclusion: SNS addiction is prevalent in undergraduate health professionals. High level of FOMO, perceived stress, and insomnia among the health professionals are important correlates with SNS addiction.

Keywords: Addiction, correlates, social media, undergraduates

How to cite this article:
Patel VK, Chaudhary P, Kumar P, Vasavada DA, Tiwari DS. A study of correlates of social networking site addiction among the undergraduate health professionals. Asian J Soc Health Behav 2021;4:30-5

How to cite this URL:
Patel VK, Chaudhary P, Kumar P, Vasavada DA, Tiwari DS. A study of correlates of social networking site addiction among the undergraduate health professionals. Asian J Soc Health Behav [serial online] 2021 [cited 2023 Dec 3];4:30-5. Available from: http://www.healthandbehavior.com/text.asp?2021/4/1/30/308810

  Introduction Top

Social networking sites (SNSs) are virtual communities where users can create individual public profiles, interact with real-life friends, and meet other people based on shared interests. SNSs are widely used for the interactions in young adults. In spite of some positive aspects associated with SNS use, its excessive use has raised a concern regarding the potential addiction of social media among its users.[1] SNS addiction has received media attention with warning that “social networking is engineered to be as habit-forming as crack cocaine,” and “Twitter is harder to resist than cigarettes and alcohol.”[2],[3]

Griffiths argues that any behavior (e.g., social networking) that fulfills the six criteria can be operationally defined as an addiction. In relation to SNS, these components are salience, mood modification, tolerance, withdrawal symptoms, conflict, and relapse.[4] Andreassen defined SNS addiction as “being overly concerned about social media, driven by an uncontrollable motivation to log on to or use social media, and devoting so much time and effort to social media that it impairs other important life areas.”[5] The latest revision of International Classification of Diseases-11 has included “gaming disorder” as new behavioral addiction.[6]

Prevalence rates of SNS addiction in India vary from 1.6% to 70% found in different studies.[7],[8] Many prior studies have explored the relationship of social media usage and mental health problems (e.g., stress, anxiety, depression, and insomnia) among the social media users.[9],[10],[11]

Although several studies have explored the factors that contributed to social media addiction in young adults, paucity of research was found in the literature regarding SNS addiction in young health professionals.[12],[13] This study seeks to bridge this gap in research by examining how multiple factors influence social media addiction.

  Methods Top

Design and setting

This was cross-sectional and observational study of the 730 health professional undergraduates from the government colleges of medical, dental, and physiotherapy. Participants were selected proportionally through each college using stratified random sampling from August 2019 to January 2020. Students were explained the study objectives, and written informed consent was taken. Participants who refuse to participate were excluded from the study.


Sociodemographic characteristics

It includes age, gender, weight, height, accommodation status, socioeconomic status, regular daily sports or exercise, and substance use. It also contains social media usage patterns such as type of social media use, time spent on social media, place and hours of usage, money spent on Internet per month, checking social media notifications, and duration of social media use in years.

Social Media Disorder Scale

The Social Media Disorder Scale (SMDS) is a nine-item structured questionnaire covering the domains of addiction such as preoccupation, tolerance, withdrawal, persistence, displacement, problem, deception, escape, and conflict during the past year. SMDS is scored with a rating of Yes/No; someone is diagnosed with having SMD if he or she meets five (or more) of the nine criteria for Internet gaming disorder during a period of 12 months.[14] This scale showed adequate reliability with a Cronbach's alpha internal consistency reliability coefficient of 0.70 for current sample.

Fear of Missing Out Scale

The Fear of Missing Out (FOMO) Scale is a collection of 10 statements about your everyday experience. Using the scale provided please indicate how true each statement is of your general experiences. Please answer according to what really reflects your experiences rather than what you think your experiences should be. Please treat each item separately from every other item. Each question is paired with a five-point Likert scale: 1 = not at all true of me, 2 = slightly true of me, 3 = moderately true of me, 4 = very true of me, and 5 = extremely true of me. The FOMO Scale has a reliable composite measure (α = 0.87–0.90).[15]

Perceived Stress Scale

The Perceived Stress Scale (PSS) is a 10-item scale individual item based on Likert scale ranging from 0 to 4. Participants with scores ranging from 0 to 13 would be low stress, 14 to 26 would be moderate stress, and 27 to 40 would be high perceived stress. PSS exhibited satisfactory psychometric property.[16]

Prior permission has been obtained regarding lecture of “problematic SNS use in health professionals” from the dean/principal of the concerned colleges. We have informed the students of particular batch about time of lecture to ensure the full attendance and then approached them later as per prior communication. We delivered the lecture on problematic SNS use and explained the study objectives and information to be filled in the pro forma to the students. As per study design, students of particular batch were randomly selected using random number table and they were requested to fill the pro forma. Students were given 20 min to complete the pro forma and at the end all the papers were collected from the students.

Sample size calculation

Sample size required for the current study was calculated using Epi-Info software, Centers for Disease Control and Prevention (CDC), Piedmont, North Carolina, United State. Sample size for the current study was estimated at 683; criteria being prevalence of disorder as 20%, 3% absolute precision, and 95% confidence interval.

Ethical consideration

Ethical approval for the present study was taken from the Institutional Ethics Committee of M P Shah Government Medical College and Guru Gobindsingh Hospital, Jamnagar (Ref. No. IEC/Certi/96/03/2019).

Statistical analysis

All the collected data were tabulated in Microsoft Excel and analyzed using statistical software “Statistical Package for Social Sciences version 20. 0.” International business machine, Armonk, New York, United States. Frequencies and percentages were computed for the sociodemographic and social media usage variables. Chi-square test was used for qualitative data. Multiple regression analysis was applied to get beta value. P < 0.05 was considered as statistically significant.

  Results Top

Out of 730 participants, 712 were included for the final analysis and the rest of 18 participants were excluded because they did not complete the study pro forma. The mean age of participants was 21.40 ± 2.15 years.

In the study population, 62.35% were female and 37.64% were male participants. 20.93% belonged to lower/lower middle class, 30.20% belonged to middle class, and 48.88% belonged to upper middle/upper class. 34% came from the rural and 64% came from the urban domicile.

The distribution of gender, domicile, socioeconomic status, daily sports/exercise, body mass index (BMI), father's education, and mother's education with the SNS addiction is depicted in [Table 1]. There was a statistically significant association found between SNS addiction and socioeconomic status, daily sports/exercise, and BMI [Table 1].
Table 1: Sociodemographic detail and social networking site addiction

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Overall, 15.02% of the health professional undergraduates reported SNS addiction. Nearly 90% of the participants were using more than one type of SNS, and among them, WhatsApp (85%), Facebook (82%), YouTube (74%), and Instagram (60%) were most commonly used social media platforms. However, the less commonly used social media platforms were Twitter (30%) and Snapchat (23%).

Out of 107 participants with SNS addiction, 83.18% were using SNS for more than 2 h in a day, 51.4% were using SNS at hostel or home, 54.21% were using SNS during leisure hours, 68.22% were using SNS since more than 5 years, and 50.47% spent more than 300 rupees per month on Internet. Distribution of SNS usage pattern and SNS addiction was statistically significant [Table 2].
Table 2: Social networking site addiction and social networking site usage pattern among the health professionals

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Out of 107 participants with SNS addiction, 40.19% reported moderate stress and 41.12% reported severe stress, 13.08% reported moderate insomnia, and 72.90% reported severe insomnia. Distribution of perceived stress, insomnia severity, and SNS addiction was statistically significant [Table 3].
Table 3: Perceived stress and insomnia severity in health professionals with social networking site addiction

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Independent variables showing statistically significant association using Chi-square test were selected for further analysis using multiple regression analysis. Perceived stress, insomnia severity, and FOMO emerged as statistically significant association with the SNS addiction [F = 426.96, P < 0.005, R2 = 0.643, Table 4].
Table 4: Multiple linear regression analysis of social networking site addiction relation with different correlates

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  Discussion Top

In the present study, the prevalence rate of SNS addiction was 15.02% among the undergraduate health professionals. The study results are consistent with finding of Wu et al.,[17] Hormes et al.,[18] and Wolniczak et al.[19] However, Alabi (2013) from Nigeria reported 1.6% Facebook addiction among undergraduates.[20] These differences could be due to the use of different methods and Internet connectivity in different geographical areas.

In the present study, no gender difference was observed among social media addiction prevalence. Most of the studies did not show any gender difference for social media addiction, while Masthi et al.,[7] Müller et al.,[21] and Goel et al.[22] found that male gender was significantly more likely to be social media addicted as compared to female gender.

In this study, participants with SNS addiction significantly spent more money and time, using SNS during leisure time and other time at hostel or home or college hours, and started SNS use early in adolescents age compared to their counter parts. Masthi et al.[7] and Bodroža and Jovanović[23] also observed similar results. Moon et al. reported the possible reason for this as to pursue feeling of achievement, make social contacts, and to enhance self-esteem among male participants.[24]

In the present study, FOMO was found to be predictor of SNS addiction on multiple regression analysis. Results of the current study have been consistent with finding of Abeele and Rooij, who observed among 3000 students that the use of problematic SNSs was affected by the FOMO.[25] Oberst et al. observed higher involvement of SNS use and feeling depressed and anxiety trigger among 5280 students.[26] Franchina et al. also reported that the FOMO acts as a stronger predictor of the use of social media platforms such as Facebook and Snapchat.[27] Even FOMO can develop a positive effect on attitude toward the SNS use.[28] If an individual's need is not satisfied, they may develop FOMO, which can lead to excessive use of SNS.[16]

In the present study, participants with SNS addiction significantly perceived moderate-to-severe stress compared to their counterpart. A study among the German students found that the perceived stress was closely related to Internet-relevant problematic behaviors, such as Facebook addiction disorder.[16],[29] Hou et al. also found that perceived stress was related to problematic SNS use.[12] Chen et al. observed the mediating effect of perceived stress and interpreted that people may choose to spend a lot of time online to cope with their stress and problems.[30] Even though there was an association between perceived stress and problematic SNS use, the exact underlying mechanism is yet not well known, resulting in hindrance of understanding the relationship between perceived stress and problematic SNS use.[31] However, previous studies also reported that depression/anxiety had a mediating effect for development of problematic SNS use.[32]

The present study showed that insomnia was emerged as a predictor of SNS. This finding is consistent with Levenson et al. who found that younger adults with higher social media had considerably greater probabilities of having sleep disorders.[33] Garett et al. observed that social media use was associated with poor sleep quality among college students.[34] Furthermore, Mohammadbeigi et al. (2016) also observed high usage of Internet, and social networks via smart cell phones are related to poor sleep quality and quantity.[35]

The present study was limited by cross-sectional design which prevents the ability to make causal inferences. This study sampled undergraduate professionals at one particular university, so results may not generalize to the wider population. The study contains self-report data that might threaten the accuracy of the statistical relationships between variables.

  Conclusion Top

SNS addiction is prevalent problem among the undergraduate health professionals. Social media usage patterns such as using SNS during most of the time including college hours, spent more time and money, and started SNS use early are some important variables related to SNS addiction. High level of FOMO, perceived stress, and insomnia among the health professionals are important correlates with SNS addiction. Educational workshop about problematic social media use should be included as a part of foundation course for the undergraduate health professionals.

Financial support


Conflicts of interest

There are no conflicts of interest.

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  [Table 1], [Table 2], [Table 3], [Table 4]

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