An Investigation of Social Status among Adolescents and Young Adults Who Have Been Diagnosed with Cancer in Canada
Bibliographic record
Abstract
BACKGROUND: Aims were to: (1) compare social status among AYAs diagnosed with cancer to a community population; (2) describe AYAs' change in employment/education status; and (3) examine predictors of social status. METHOD: Social status (i.e., education, employment, relationship status, and living arrangement) was captured from young adults diagnosed with cancer recruited via social media through a community-based organization from across Canada and randomly matched to a community sample by sex, age, province of residence, total household income and race/ethnicity at a ratio of 1:3. RESULTS: < 0.001). There were no differences in education or relationship status. Overall, 41% and 45% of AYAs reported quitting school or work, respectively. Non-metastatic disease (AOR 3.23, 95% CI 1.08-9.62), and better physical (AOR 1.07 95% CI 1.04-1.10) and mental quality of life (QOL)(AOR 1.06 95% CI 1.03-1.09), were associated with employment. Worse mental QOL (AOR 1.04 95% CI 1.01-1.07), less post-traumatic growth (AOR 1.01 95% CI 1.00-1.03), and social support (AOR 0.27, 95% CI 0.18-0.41) were associated with being single. Non-White race (AOR 3.19 95% CI 1.02-9.97) and less post-traumatic growth (AOR 0.97 95% CI 0.95-0.99) were associated with living with parents. CONCLUSIONS: AYAs diagnosed with cancer experience differences in attainment of employment and independent living compared to a community sample. These challenges may have implications for physical and mental QOL.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".