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Record W2055407174 · doi:10.1207/s15326888chc3203_3

Developmental Differences in Psychological Adjustment and Health-Related Quality of Life in Pediatric Cancer Patients

2003· article· en· W2055407174 on OpenAlexfundno aff
Maru Barrera, Leigh-Ann Wayland, Norma Mammone D’Agostino, Julie Gibson, Rosanna Weksberg, David Malkin

Bibliographic record

VenueChildren s Health Care · 2003
Typearticle
Languageen
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsnot available
FundersMedical Research Council Canada
KeywordsTemperamentQuality of life (healthcare)MedicineClinical psychologyPediatric cancerHealth related quality of lifeCancerPsychologyPersonalityDiseaseInternal medicine

Abstract

fetched live from OpenAlex

The aims of this study were to investigate: (a) age differences in psychological adjustment (PA) and health-related quality of life (HRQOL) in pediatric cancer patients, and (b) identify predictors of PA and HRQOL. The sample included preschool, school age, and adolescent patients. Data were obtained at 3 (n = 69), 9 (n = 47), and 15 (n = 44) months after diagnosis, using standardized measures completed by the mother. Measures assessed the children's psychological adjustment (PA), health-related quality of life (HRQOL), temperament and maternal psychological adjustment. Age at diagnosis significantly affected both PA and HRQOL. At 3 months post-diagnosis, preschoolers had more externalizing behavior problems than did adolescents. Preschoolers had better HRQOL than adolescents at all 3 assessments. Maternal adjustment and child's temperament scores were the best predictors of PA; age was the best predictor of HRQOL. The results of this study suggest that preschoolers with cancer are at risk for behavior problems and adolescents are at risk for poor HRQOL. The results also highlight the importance of multi-factor models in predicting children's PA and HRQOL.

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)0.001
metaresearch head score (Gemma)0.000
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 score0.030
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.062
GPT teacher head0.381
Teacher spread0.319 · 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

Citations41
Published2003
Admission routes1
Has abstractyes

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