Digital self-presentation and adolescent mental health: Cross-sectional and longitudinal insights from the “LifeOnSoMe”-study
Bibliographic record
Abstract
BACKGROUND: The intensive use of social media among adolescents has caused concern about its impact on their mental health, but studies show that social media use is linked to both better and worse mental health. These seemingly contradictory findings may result from the diverse motivations, interactions, and experiences related to social media use, and studies investigating specific facets of social media use in relation to mental health and well-being, beyond general usage metrics, have been called for. Aspects of self-presentation on social media, such as feedback-seeking and upwards social comparison have been linked to worse mental health, however, there is a need for more studies exploring the relationship between self-presentation on social media and adolescent mental health over time. AIM: The aim of this study was to explore the cross-sectional and longitudinal relationship between aspects of self-presentation and depression, anxiety, and well-being among adolescents. METHODS: This study utilised both cross-sectional and longitudinal datasets from the LifeOnSoMe-study, comprising 3,424 and 439 participants, respectively (OSF preregistration https://doi.org/10.17605/OSF.IO/BVPS8 ). Latent Class Analysis (LCA) was used to identify similar response patterns within the Self-Presentation and Upwards Social Comparison Inclination Scale (SPAUSCIS). Regression models and first differencing methods were applied to evaluate the cross-sectional and longitudinal associations between focus on self-presentation and mental health and well-being among adolescents. RESULTS: A strong emphasis on self-presentation was linked to increased levels of depression and anxiety in both males and females, and reduced well-being in females when compared to those with lower or intermediate self-presentation focus. The effect sizes ranged from small to medium. Furthermore, an escalation in self-presentation focus over time was associated with a slight increase in symptoms of anxiety and depression; however, the association with well-being did not reach statistical significance. CONCLUSION: The results of the present study suggest that a heightened focus on self-presentation, which includes behaviours such as seeking feedback, employing strategic self-presentation tactics, and engaging in upward social comparisons, is associated with an elevated risk of reduced mental health.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".