Adolescent empathic concern and perspective taking: Heterogeneous developmental trajectories and childhood social and psychological factors
Bibliographic record
Abstract
OBJECTIVE: The joint developmental trajectories of empathic concern and perspective taking were examined across adolescence, along with childhood social and psychological predictors. METHOD: Adolescents completed self-report measures of empathy annually from Grades 7 to 10 (i.e., ages 13 to 16; N = 609; 53.9% girls; 76.2% White). Childhood social and psychological predictors were assessed in Grades 5 and 6 using self- and parent-reports. RESULTS: As predicted, the majority of individuals reflected a joint trajectory of moderate stable empathic concern and moderate increasing perspective taking (31.9%), followed by joint high increasing (17.2%) and joint low stable (7.4%) empathy. Fewer adolescents reflected joint trajectories of being high on one form of empathy but not the other (e.g., high empathic concern only, 1.6%; high increasing perspective taking only, 2.8%). High increasing perspective taking was a better indicator of high increasing empathic concern than the reverse. Higher childhood hyperactivity, higher bullying perpetration, and lower perceived school climate were prominent predictors of developing low levels of at least one form of empathy, but childhood anxiety was a predictor of developing high empathy. CONCLUSIONS: The skills and abilities associated with perspective taking and empathic concern should be promoted, with special attention paid to early indicators of affective, cognitive, and behavioral self-regulation.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".