A Review of the Relationship Between Social Media Use and Online Prosocial Behavior Among Adolescents
Bibliographic record
Abstract
Social media (SoMe) activity constitutes a large part of the lives of adolescents. Even though the behavior on SoMe is complex, the research on SoMe has mostly focused on negative effects, bad content, and online antisocial behavior (OAB). Less research has been conducted on online prosocial behavior (OPB), and to what extent OPBs are widespread is relatively unknown. A review was conducted to investigate to what extent OPB is related to SoMe use among adolescents based on studies published from 2014 to May 2021. To be included, the studies had to be quantitative, non-experimental, have participants aged 13–18, include measures of SoMe and OPB, and be published in peer-reviewed journals with full text available in English, Swedish, Danish or Norwegian. A research was conducted in databases PsychINFO, Ovid MEDLINE(R), EMBASE, COCHRANE Database of Systematic Reviews, Web of Science, Sociological Abstracts, Sociological Services Abstracts, and Eric. Two studies met the eligibility criteria. Both studies found an association between OPB and SoMe use. Methodological issues, however, were identified through a quality assessment using an adapted version of the Newcastle-Ottawa Scale (NOS) for cross-sectional studies, and the small samples in the studies prevent us from drawing any firm conclusions. Possible reasons for the scarcity of eligible studies and directions for future research are discussed. Systematic Review Registration: PROSPERO; ID CRD42020162161 and CRISTIN; ID 2038994.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.013 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 source (direct Gemma or distilled Codex), 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".