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Record W2473473624 · doi:10.1097/dbp.0000000000000315

Social Competence in Childhood Brain Tumor Survivors: Feasibility and Preliminary Outcomes of a Peer-Mediated Intervention

2016· article· en· W2473473624 on OpenAlexaff
Katie A. Devine, William M. Bukowski, Olle Jane Z. Sahler, Pamela Ohman‐Strickland, Tristram H. Smith, E. Anne Lown, Andrea Farkas Patenaude, David N. Korones, Robert B. Noll

Bibliographic record

VenueJournal of Developmental & Behavioral Pediatrics · 2016
Typearticle
Languageen
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsConcordia University
FundersNational Cancer Institute
KeywordsIntervention (counseling)Competence (human resources)Social competencePsychologyPeer groupBrain tumorMedicineClinical psychologyDevelopmental psychologyPsychiatrySocial psychologySocial change

Abstract

fetched live from OpenAlex

OBJECTIVE: Evaluate the acceptability, feasibility, and preliminary outcomes of a peer-mediated intervention to improve social competence of brain tumor survivors and classmates. METHOD: Twelve childhood brain tumor survivors and 217 classroom peers in intervention (n = 8) or comparison (n = 4) classrooms completed measures of social acceptance and reputation at 2 time points in the year. The intervention (5-8 sessions over 4-6 weeks) taught peer leaders skills for engaging classmates. Individual and classroom outcomes were analyzed with analysis of covariance. RESULTS: Recruitment rates of families of brain tumor survivors (81%) and schools (100%) were adequate. Peer leaders reported satisfaction with the intervention. Preliminary outcome data trended toward some benefit in increasing the number of friend nominations for survivors of brain tumors but no changes in other peer-reported metrics. Preliminary results also suggested some positive effects on classroom levels of victimization and rejection. CONCLUSION: A peer-mediated intervention was acceptable to families of brain tumor survivors and feasible to implement in schools. Findings warrant a larger trial to evaluate improvements for children with brain tumors and their peers.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.812

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.046
GPT teacher head0.351
Teacher spread0.305 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations27
Published2016
Admission routes1
Has abstractyes

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