Social Outcomes in the Childhood Cancer Survivor Study Cohort
Bibliographic record
Abstract
Difficulties with negotiating and achieving desired social outcomes in life may be exacerbated by the experience of childhood cancer, including adverse effects from therapies used to achieve a cure. This review of previous publications from the Childhood Cancer Survivor Study (CCSS) and other relevant literature provides insight into the prevalence of, and risk factors for, poor educational attainment, less than optimal employment status, and interpersonal relationship issues among long-term survivors of childhood cancer. The impacts of emotional health and physical disability on social outcomes are also examined. Study results suggest that childhood cancer survivors generally have similar high school graduation rates, but are more likely to require special education services than sibling comparison groups. Survivors are slightly less likely than expected to attend college, and are more likely to be unemployed and not married as young adults. Cancers and treatments that result in impairment to the CNS, particularly brain tumors, or that impact sensory functioning, such as hearing loss, are associated with greater risk for undesirable social outcomes, as are emotional health problems and physical disability. This review of relevant data from CCSS and other studies provides information on risk factors for social problems into adulthood. A greater understanding of the long-term social impacts from the diagnosis and treatment of childhood cancer is critically important for developing targeted interventions to prevent or ameliorate adverse psychosocial effects.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".