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Financial hardship and non-adherence to lifestyle and surveillance recommendations in adult survivors of childhood cancer: A report from the Childhood Cancer Survivor Study (CCSS).

2025· article· en· W4410805263 on OpenAlexaff
Neel S. Bhatt, Fang Wang, Shizue Izumi, Yan Chen, Gregory T. Armstrong, I‐Chan Huang, Anne C. Kirchhoff, K. Robin Yabroff, Yutaka Yasui, Paul C. Nathan

Bibliographic record

VenueJournal of Clinical Oncology · 2025
Typearticle
Languageen
FieldHealth Professions
TopicAdolescent and Pediatric Healthcare
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsMedicineCancerChildhood cancerCancer survivorGerontologyFamily medicineInternal medicine

Abstract

fetched live from OpenAlex

10068 Background: The association between different aspects of medical financial hardship and non-adherence to healthy lifestyle recommendations and surveillance for subsequent neoplasms (SN) and cardiomyopathy in long-term survivors of childhood cancer is unknown. Methods: A randomly selected subset of participants in the CCSS completed a financial hardship survey and a follow-up survey assessing lifestyle behaviors and adherence to recommended surveillance. Presence of financial hardship was determined by affirmative response to ≥1 item in material (e.g., high out-of-pocket costs), behavioral (e.g., delaying care due to cost), or psychological (e.g., worry about financial situation) hardship domains. Outcomes included “not meeting physical activity guidelines” ( < 9 metabolic-equivalent-of-task-hour/week moderate to vigorous activity), “problematic drinking” ( > 7 drinks/week or > 3 drinks/day [women], > 14 drinks/week or > 4 drinks/day [men]), current smoker, unhealthy BMI ( < 18.5 or ≥30 kg/m 2 ), and non-adherence to surveillance for breast, colorectal, and/or skin cancer, and cardiomyopathy screening according to the Children’s Oncology Group guidelines. Logistic regression models, adjusted for age at the most recent survey, sex, race/ethnicity, education, and chronic health conditions, examined the association of material, behavioral, and psychological hardship with healthy lifestyle and surveillance outcomes. Results: A total of 3,322 survivors, at a median of 34.4 (range:19.7-51.4) years from diagnosis and 41 (20-69) years of age at the most recent survey were included. Presence of material hardship alone was associated with higher risk of not meeting physical activity guidelines (odds ratio 1.6, 95%CI 1.2-2.1) and unhealthy BMI (1.4, 1.1-1.8). Presence of both material and behavioral (1.8, 1.2-2.6) or material and psychological (1.8, 1.4-2.4) hardships further increased the risk for unhealthy BMI. Presence of all 3 hardship domains was associated with higher risk of unhealthy BMI (2.2, 1.8-2.7). Behavioral hardship (2.2, 1.1-4.6) and psychological hardship (3.9, 2.4-6.4) alone were associated with higher risk of being a current smoker at time of follow-up, with presence of both further increasing the risk for smoking (4.1, 2.3-7.3). Presence of psychological hardship alone was associated with higher non-adherence to cardiomyopathy screening (1.3, 1.0-1.8) among those at high risk. Associations between hardship and SN surveillance were not significant. Conclusions: Financial hardship is associated with non-adherence to healthy lifestyle and recommended screening for cardiomyopathy among adult survivors of childhood cancer. Findings underscore the need for strategies to identify and mitigate financial hardship and improve adherence to recommended lifestyle and surveillance.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.033
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.109
GPT teacher head0.533
Teacher spread0.424 · 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 source (direct Gemma or distilled Codex), 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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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