The Age Conundrum: A Scoping Review of Younger Age or Adolescent and Young Adult as a Risk Factor for Clinical Distress, Depression, or Anxiety in Cancer
Bibliographic record
Abstract
This scoping review was conducted to understand the extent, range, and nature of current research on adolescents and young adults (AYA) with cancer and distress, depression, and anxiety (DDA). This information is necessary to find and aggregate valuable data on the AYA population embedded in generalized studies of DDA. Keyword searches of six relevant electronic databases identified 2156 articles, with 316 selected for abstract review and 40 for full text review. Full-text reviews and data extraction resulted in 34 studies being included, which ranged widely in design, sample size, age-range categorization, analysis methods, DDA measurement tool, overall study rigor, and quality of evidence. Studies very seldom reported using theory to guide their age categorization, with only four studies giving any rationale for their age-group definitions. All 34 studies found a significant association between at least one DDA construct and the younger age group relative to the older age groups at some point along the cancer trajectory. However, age as an independent risk factor for DDA is still unclear, as the relationship could be confounded by other age-related factors. Despite the wide range of definitions and effect sizes in the studies included in this review, one thing is clear: adolescents and young adults, however defined, are a distinct group within the cancer population with an elevated risk of DDA. Widespread adoption of a standard AYA age-range definition will be essential to any future meta-analytical psycho-oncology research in this population.
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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 | 0.030 | 0.124 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.008 |
| Bibliometrics | 0.018 | 0.017 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".