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Record W2411916872 · doi:10.1002/cncr.30106

Patterns and predictors of clustered risky health behaviors among adult survivors of childhood cancer: A report from the Childhood Cancer Survivor Study

2016· article· en· W2411916872 on OpenAlexaff
E. Anne Lown, Nobuko Hijiya, Nan Zhang, Deo Kumar Srivastava, Wendy M. Leisenring, Paul C. Nathan, Sharon M. Castellino, Katie A. Devine, Kimberley Dilley, Kevin R. Krull, Kevin C. Oeffinger, Melissa M. Hudson, Gregory T. Armstrong, Leslie L. Robison, Kirsten K. Ness

Bibliographic record

VenueCancer · 2016
Typearticle
Languageen
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsHospital for Sick Children
FundersNational Cancer InstituteAmerican Lebanese Syrian Associated Charities
KeywordsMedicineOdds ratioConfidence intervalCluster (spacecraft)DemographyLogistic regressionEducational attainmentChildhood cancerCancerDistressGerontologyClinical psychologyInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Health complications related to childhood cancer may be influenced by risky health behaviors (RHBs), particularly when RHBs co-occur. To the authors' knowledge, only limited information is available describing how RHBs cluster among survivors of childhood cancer and their siblings and the risk factors for co-occurring RHBs. METHODS: Latent class analysis was used to identify RHB clusters using longitudinal survey data regarding smoking, alcohol use, and physical activity from adult survivors (4184 survivors) and siblings (1598 siblings) in the Childhood Cancer Survivor Study. Generalized logistic regression was used to evaluate associations between demographic characteristics, treatment exposures, psychological distress, health conditions, and cluster membership. RESULTS: Three RHB clusters were identified: a low-risk cluster, an insufficiently active cluster, and a high-risk cluster (tobacco and risky alcohol use and insufficient activity). Compared with siblings, survivors were more likely to be in the insufficiently active cluster (adjusted odds ratio [ORadj ], 1.17; 95% confidence interval [95% CI], 1.06-1.27) and were less likely to be in the high-risk cluster (ORadj , 0.79; 95% CI, 0.69-0.88). Risk factors for membership in the high-risk cluster included psychological distress (ORadj , 2.76; 95% CI, 1.98-3.86), low educational attainment (ORadj , 7.49; 95% CI, 5.15-10.88), income <$20,000 (ORadj , 2.62; 95% CI, 1.93-3.57), being divorced/separated or widowed (ORadj , 1.36; 95% CI, 1.03-1.79), and limb amputation (ORadj , 1.52; 95% CI, 1.03-2.24). Risk factors for the insufficiently active cluster included chronic health conditions, psychological distress, low education or income, being obese or overweight, female sex, nonwhite race/ethnicity, single marital status, cranial radiation, and cisplatin exposure. CONCLUSIONS: RHBs co-occur in survivors of childhood cancer and their siblings. Economic and educational disadvantages and psychological distress should be considered in screening and interventions to reduce RHBs. Cancer 2016. © 2016 American Cancer Society. Cancer 2016;122:2747-2756. © 2016 American Cancer Society.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.095
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.316
Teacher spread0.297 · 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.

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

Citations39
Published2016
Admission routes1
Has abstractyes

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