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Record W2979605743 · doi:10.1080/07347332.2019.1664702

Posttraumatic growth and its correlates among survivors of adolescent and young adult cancer: A brief report

2019· article· en· W2979605743 on OpenAlexaff
Meagan Barrett-Bernstein, Amanda Wurz, Jennifer Brunet

Bibliographic record

VenueJournal of Psychosocial Oncology · 2019
Typearticle
Languageen
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsOttawa HospitalInstitut du Savoir MontfortUniversity of CalgaryMontfort HospitalUniversity of Ottawa
Fundersnot available
KeywordsPosttraumatic growthBivariate analysisClinical psychologyYoung adultDescriptive statisticsPsychologyMedicineGerontologyDevelopmental psychology

Abstract

fetched live from OpenAlex

Objectives: The objectives of this study were to describe posttraumatic growth (PTG) levels among survivors of adolescent and young adult cancer (AYAs), and estimate relationships between PTG and medical (cancer type, age at diagnosis, time since treatment), behavioral (physical activity), and psychological (appearance evaluations, body satisfaction) variables.Methods: Eighty-eight AYAs (Mage=33 ± 4.4 years) completed a survey online that included the PTG-Inventory (PTG-I). Data were analyzed using descriptive statistics and bivariate correlations.Findings: Total and subdimension PTG-I scores indicated moderate-to-high PTG levels, with the highest and lowest scores reported for appreciation of life and spiritual change, respectively. Appearance evaluations was moderately and positively correlated with the spiritual change subdimension (r = .31, p < .001). Relationships between PTG and other variables were of weak magnitude and not statistically significant (rs = 0–.21, ps > .05).Conclusions: More research exploring variables related to PTG among AYAs is needed to better understand antecedents and outcomes of PTG.

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 score0.012
Threshold uncertainty score0.685

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.019
GPT teacher head0.337
Teacher spread0.318 · 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

Citations7
Published2019
Admission routes1
Has abstractyes

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