The other side of the screen: The impact of perspective‐taking on adolescents’ online communication
Bibliographic record
Abstract
INTRODUCTION: In recent decades, adolescents' interactions with peers have increasingly transitioned online. While socially interactive technologies provide multiple avenues for positive communication between peers, adolescents may experience harmful online peer interactions, with such interactions negatively impacting their well-being. A paucity of work exists investigating how adolescents' characteristics are related to their communicative choices on social media and if such choices can be influenced by cues to consider a recipient. Addressing this gap, this work examines experimental manipulations of perspective-taking and individual differences in socio-cognitive skills as they relate to adolescents' communicative choices online. METHOD: Within individual sessions, 12- to 15-year-old Canadian participants (N = 72, 36 girls) viewed pictures of other adolescents on a simulated social media app similar to Snapchat and chose between pre-written aggressive or prosocial comments to send to a recipient under three conditions: a perspective-taking cue, a time-delay, no delay. Participants also completed self-report questionnaires assessing emotion regulation and empathy. RESULTS: Following perspective-taking cues, participants chose more prosocial comments to send compared to when participants were permitted to choose a comment immediately after viewing another adolescent's picture, while controlling for a brief time-delay. Adolescents' individual characteristics (i.e., Social Media Use, State Mood, Affective Empathy, Gender) were associated with their communicative choices online. CONCLUSIONS: Findings from this work provide new insight into the ways adolescents navigate their complex and increasingly online peer interactions. Further, the results suggest that adolescents' social media communication is malleable with a brief perspective-taking cue to consider a recipient.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".