Social media usage and depressive symptoms among adolescents in India

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In a recently published study, Dr BMC Public Health, Researchers investigated the possible bidirectional association between social media use and depressive symptoms among adolescents in India.

They used aggregated data from the Lives of Adolescents and Young Adults (UDAYA) project survey conducted in Uttar Pradesh and Bihar from 2015-16 (Wave 1) to 2018-19 (Wave 2) for this survey.

Study: Bidirectional and cross-lag relationships between social media use and psychological well-being: Evidence from an Indian adolescent cohort study.  Image credit: 1st footage/
Study: Bidirectional and cross-lag relationships between social media use and psychological well-being: Evidence from an Indian adolescent cohort study.. Image credit: 1st footage/


Social media greatly influences teenagers and young adults. However, there is a critical gap in the existing research on the effects of social media use on young adolescents’ mental health, which primarily includes cross-sectional studies from Western countries.

There is a lack of understanding of how this trend changes over time and how it manifests in developing countries like India, which had 518 million social media users in 2020, expected to grow to ~1.5 billion by 2040.

About the study

In the current study, researchers longitudinally tracked changes in social media use and its effects on the mental health of Indian adolescent boys and girls over a three-year period.

They first evaluated its immediate effects in a within- and between-subjects analysis; Next, they investigated the bidirectional relationship across its developmental stages, allowing for a broader examination of the relationship between social media use and depression.

The study population included young and older adolescents aged 10–14 and 15–19 years, respectively. They were interviewed at baseline (Wave 1) and followed up in 2018–19 (Wave 2) when they reached the ages of 13–17 and 18–22, respectively, to shed light on the factors that determine successful transition to adulthood. and establish levels, patterns and trends in their circumstances.

The team assessed depression symptoms in the teens using just nine questions over the past two weeks, which they rated on a scale of four, and STATA 14 produced a total score out of 27, which helped the team categorize depression symptoms into four categories: no, mild, moderate. and serious. Similarly, they assess the frequency and duration of social media use.

Predictor variables measured at wave 1 were age, gender, mother’s education and wealth index. Variables measured in both Waves 1 and 2 were current schooling, paid work, substance use, and social media use.

Further, the team used binary logistic regression to analyze the association between depression and these variables, including social media use. They conducted a longitudinal cross-lagged path analysis to examine the bidirectional relationship between social media use and depressive symptoms in adolescents.

The team applied five models to assess the bidirectional effects of social media use and psychological well-being over time. Finally, they determined the best-fitting model using various criteria such as chi-square value, Akaike information criterion (AIC), comparative fit index (CFI), root mean square error of approximation (RMSEA) and chi-square difference testing. . , where, for example, CFI of 0.95 or greater and RMSEA of 0.05 or less indicate the best fitting model.


The sample size for the current study was 4,428 boys and 7,607 girls (12,035 adolescents) aged 10–19 years at Wave 1 and 4,428 adolescent boys and 11,864 adolescent girls (16,292 adolescents) aged 13–223 years.

Survey results showed that Internet access among adolescent boys and girls increased from Wave 1 to Wave 2 (25.3% to 70.2% and 6.6% to 38.5%), which, in turn, increased their social media use with a significant difference. between boys and girls (13.9% to 57.6% and 3.8% to 26.6%).

From Wave 1 to Wave 2, a higher percentage of adolescent girls experienced mild to severe depressive symptoms, whereas mild depressive symptoms increased slightly among boys compared to girls from Wave 1 to Wave 2 (5.9% to 7.3% vs. 12.6% to 18.4%). This vulnerability of adolescents is attributed to the social pressures they go through in the digital world.

In logistic regression analysis, age emerged as a significant predictor of adolescent symptoms during adolescence; Adolescents aged 15–19 years were twice as likely to have depressive symptoms as their younger counterparts, OR = 2.762.

Education acts as a barrier to depression; Thus, educated teenagers were less depressed than uneducated ones. Similarly, wealthy teenagers were more likely to be depressed than their poorer counterparts.

Furthermore, those who engaged in paid work and substance abuse in the past year were 18% and 57% more likely to have depressive symptoms, respectively. Additionally, dropping out of school was associated with an increased likelihood of depression.

Furthermore, compared to social media non-users, frequent social media users (three or more hours per day) were more likely to be depressed.


Overall, the present study found a significant cross-sectional correlation between social media use and depression among adolescent boys and girls in India. Factors such as age, gender and education showed significant associations with this association.

This study, thus, warrants future studies exploring this association based on the time, purpose, and type of social media used with mental health problems other than depression.

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