Depressive symptoms in adolescents can be influenced by their social media experiences. Engaging with negative content or making unhealthy comparisons on social media may exacerbate depressive symptoms.
Conversely, depressive symptoms could lead to seeking out negative content. The relationship between social media use and depressive symptoms is complex.
Brimmel, N., Bijttebier, P., & Eggermont, S. (2024). Associations between intentions for affective social media content choices and depressive symptoms in adolescence: A cross-sectional investigation of media response styles as moderators. Psychology of Popular Media, 13(4), 550–559. https://doi.org/10.1037/ppm0000510
Key Points
- Intentions for sad social media content choices in a sad mood were associated with higher levels of concurrent depressive symptoms in adolescents.
- Media dampening and rumination were associated with higher depressive symptoms. Media enhancing was associated with lower depressive symptoms.
- The relationship between intentions for happy social media content choices in a happy mood and depressive symptoms was moderated by media enhancing. High media enhancing strengthened the positive association.
Rationale
Social media plays a central role in adolescents’ lives at a time when they are also vulnerable to developing depressive symptoms (Avenevoli et al., 2015; Ivie et al., 2020).
Rather than focusing on frequency of social media use, recent research has started examining how affective experiences with social media relate to well-being (Baker & Algorta, 2016; Feinstein et al., 2013; Vahedi & Zannella, 2021).
This study aimed to understand the relationship between intentions for mood-related affective social media content choices and depressive symptoms in adolescents.
It also explored whether this relationship was moderated by media response styles – trait-like ways individuals respond to the emotional valence of media content.
The findings provide insight into subjective social media experiences that may put adolescents at risk for depressive symptoms.
Method
Cross-sectional online survey with Belgian adolescents aged 14-19.
Procedure
Participants completed online questionnaires at home measuring intentions for mood-related social media content choices, media response styles, and depressive symptoms.
Sample
157 adolescents (65.6% girls), average age 16.63 years. Majority were academic students.
Measures
- Mood-Media Content Selections Scale: Measured intentions to choose happy/sad social media content in happy/sad moods
- Center for Epidemiologic Studies Depression Scale (CES-D): Measured depressive symptoms
- Media Response Style Questionnaire for Adolescents for Negative/Positive Affective Media Content (MRSQ-A-NAM/PAM): Measured media rumination, distraction, dampening, enhancing
Statistical measures
Pearson correlations and hierarchical regressions with interaction terms.
Results
Intentions for sad social media choices in a sad mood predicted higher depressive symptoms.
Media distraction predicted lower depressive symptoms; media rumination predicted higher depressive symptoms.
The relationship between happy social media choices in a happy mood and depressive symptoms was moderated by media enhancing. The association was stronger at high levels of media enhancing.
Insight
This study highlights that adolescents’ subjective experiences with social media, not just frequency of use, relate to their emotional well-being.
Intending to select sad social media content when feeling sad was linked to more depressive symptoms, while intending to select happy content was not protective.
Trait-like responses to emotional media content had direct relationships with depressive symptoms.
Excessively thinking about feeling happy while consuming positive media content was surprisingly associated with poorer well-being.
The findings underscore the importance of understanding adolescents’ motivations and emotional experiences related to their social media use.
Teaching healthy ways to regulate emotions, both in real life and on social media, may be beneficial.
Implications
The results suggest considering the emotional valence of social media content adolescents gravitate towards when examining social media effects on well-being.
Interventions could aim to reduce ruminating on negative social media content.
The maladaptive media response styles consistently related to depressive symptoms, implying they may be important targets for improving adolescent emotional health in the social media context.
Strengths
This study had several methodological strengths, including:
- Novel examination of mood-related social media content intentions
- Considered trait-like emotional responses to social media content
- Focused specifically on adolescent population
- Used validated measures for key constructs
- Tested moderation effects of media response styles
Limitations
This study also had several methodological limitations, including:
- Small sample size limits generalizability
- Cross-sectional design precludes causal conclusions
- Measurements of social media intentions may not fully capture real-life behaviors
- Self-report measures susceptible to biases
- Did not account for different types of social media platforms
- Lacked objective data on actual social media usage
- Did not consider potential bidirectional relationships between variables
References
Primary reference
Brimmel, N., Bijttebier, P., & Eggermont, S. (2024). Associations between intentions for affective social media content choices and depressive symptoms in adolescence: A cross-sectional investigation of media response styles as moderators. Psychology of Popular Media, 13(4), 550–559. https://doi.org/10.1037/ppm0000510
Other references
Avenevoli, S., Swendsen, J., He, J. P., Burstein, M., & Merikangas, K. R. (2015). Major depression in the national comorbidity survey–adolescent supplement: Prevalence, correlates, and treatment. Journal of the American Academy of Child & Adolescent Psychiatry, 54(1), 37–44.e2. https://doi.org/10.1016/j.jaac.2014.10.010
Baker, D. A., & Algorta, G. P. (2016). The relationship between online social networking and depression: A systematic review of quantitative studies. Cyberpsychology, Behavior, and Social Networking, 19(11), 638–648. https://doi.org/10.1089/cyber.2016.0206
Feinstein, B. A., Hershenberg, R., Bhatia, V., Latack, J. A., Meuwly, N., & Davila, J. (2013). Negative social comparison on Facebook and depressive symptoms: Rumination as a mechanism. Psychology of Popular Media Culture, 2(3), 161–170. https://doi.org/10.1037/a0033111
Ivie, E. J., Pettitt, A., Moses, L. J., & Allen, N. B. (2020). A meta-analysis of the association between adolescent social media use and depressive symptoms. Journal of Affective Disorders, 275(8), 165–174. https://doi.org/10.1016/j.jad.2020.06.014
Vahedi, Z., & Zannella, L. (2021). The association between self-reported depressive symptoms and the use of social networking sites (SNS): A meta-analysis. Current Psychology, 40(5), 2174–2189. https://doi.org/10.1007/s12144-019-0150-6
Keep Learning
- Why might intending to select sad social media content when feeling sad relate to more depressive symptoms in adolescents? What are some alternate explanations besides social media causing the depressive symptoms?
- The study found that excessively focusing on feeling happy while consuming positive social media content was associated with greater depressive symptoms. Why might this be the case? Can you think of real-life examples where focusing too much on positive feelings could backfire?
- If you were designing an intervention to improve adolescent emotional health in the social media era based on these findings, what would be some key components you would include? How would you motivate adolescents to participate?
- The study focused on Instagram and Facebook as examples of social media platforms. How might the findings differ for other popular social media apps used by today’s adolescents, like TikTok, Snapchat, or BeReal? What unique features of each platform could potentially impact the results?
- Discuss the challenges of accurately measuring social media intentions and behaviors through self-report questionnaires. How could future studies use more objective measurements to capture adolescents’ real-time experiences while engaging with social media content?
