Tumor surveillance for children and adolescents with cancer predisposition syndromes: The psychosocial impact reported by adolescents and caregivers
Bibliographic record
Abstract
PURPOSE: Individuals with cancer predisposition syndromes (CPS) are often followed in cancer screening programs, which aim to detect early stage tumors. While cancer surveillance has the potential to improve patient outcomes, its psychosocial impact is uncharacterized in the pediatric population. We examined the cancer surveillance experience from the perspectives of adolescents and parents of children at risk of developing cancer. PATIENTS AND METHODS: Using grounded theory and thematic analysis qualitative methodology, we conducted semi-structured interviews with parents and adolescents, separately. Interviews were transcribed verbatim and coded separately to derive overlapping and unique themes. RESULTS: We completed 20 semi-structured interviews (11 parents and nine adolescents). Positive experiences were related to feelings of reassurance and taking a proactive approach. Both adolescents and parents experienced worry, related to practical aspects of screening, and related to the reminder of cancer risk that manifests with surveillance appointments. This worry was cyclical, associated with appointments, and generally waned over time. Participants felt that the benefits of surveillance outweighed perceived challenges. Open communication with health care providers, and equipping parents/adolescents with vocabulary to discuss their diagnosis and care with others, were felt to be important for mitigating worries associated with cancer risk and surveillance. CONCLUSION: Parents and adolescents experience worry associated with surveillance for CPS, which may warrant regular psychosocial support, particularly during the first year following CPS diagnosis. Enhancing communication with the health care team and among and beyond immediate family members represents an additional important strategy to mitigate adverse experiences and perceptions.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".