Are active and passive social media use related to mental health, wellbeing, and social support outcomes? A meta-analysis of 141 studies
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract The relationships between active (e.g., creating content) and passive (e.g., scrolling) social media (SM) use (SMU) and mental health, wellbeing, and social support outcomes have received significant attention, yet findings have been mixed. We conducted a meta-analysis of 141 studies (N ≈ 145,000) containing 897 effect sizes (ESs) between active and passive SMU and 13 outcomes. Most ESs were negligible (|r| < .10), with the exception of between-person associations for active SMU and greater online support (r = .34), wellbeing (r = .15), positive affect (r = .11), and symptoms of anxiety (r = .12), and passive SMU and greater online support (r = .15). Moderator analyses revealed that passive use was associated with worse emotional outcomes in general SM contexts, but not in the context of SM groups. User age also emerged as an important contextual factor. Implications for future research, theory development, and healthy SMU are discussed.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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 it