Social Self-Perception Among Pediatric Brain Tumor Survivors Compared With Peers
Bibliographic record
Abstract
OBJECTIVE: To assess self-perceptions of social behavior among children treated for a brain tumor and comparison children. To investigate group differences in the accuracy of children's self-perceptions as measured by discrepancies between self and peer reports of social behavior and to understand if these phenomena differ by gender. METHOD: Self and peer reports of social behavior were obtained in the classrooms of 116 children who were treated for an intracranial tumor. Social behaviors were assessed using the Revised Class Play, which generates indices for 5 behavioral subscales: Leadership-popularity, Prosocial, Aggressive-disruptive, Sensitive-isolated, and Victimization. A child matched for gender, race, and age was selected from each survivor's classroom to serve as a comparison. Abbreviated IQ scores were obtained in participants' homes. RESULTS: Relative to comparison children, those who had undergone treatment for a brain tumor overestimated their level of Leadership-popularity and underestimated levels of Sensitive-isolated behaviors and Victimization by peers. Female survivors were more likely than male survivors to underestimate Sensitive-isolated behaviors and Victimization. CONCLUSION: Following treatment for a brain tumor, children (particularly girls) may be more likely than healthy children to underestimate peer relationship difficulties. These discrepancies should be considered when obtaining self-report from survivors and developing interventions to improve social functioning.
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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".