133: Are They Expecting Too much? – Unrealistic Expectations About Adult Healthcare in Teenaged Childhood Cancer Survivors
Bibliographic record
Abstract
With advancements in therapies, most children diagnosed with cancer will survive their initial malignancy. However, they are at risk of developing various treatment-related late effects that can manifest years after completion of therapy. Long-term follow-up (LTFU) care is crucial to the identification and management of late effects in childhood cancer survivors. Yet, research shows that many survivors fail to transfer to LTFU after discharge from a pediatric setting or subsequently drop out as adults. For some patients, the differences encountered in the delivery and organization of care between pediatric and adult centres may act as barriers to attendance in LTFU care. Recognizing that many differences exist between pediatric and adult care services, we aim to describe adolescent childhood cancer survivors' beliefs/expectations about the nature of adult healthcare. Survivors of cancer in childhood or adolescence, between 15 to 19 years of age, who had not yet transitioned to adult LFTU cancer care, were recruited either in person or through mail. Participants completed a questionnaire which included a demographic survey and a newly developed ‘Expectations scale’. The scale contains 12 items designed to measure survivors' expectations about the nature of adult LTFU care and has been found to be psychometrically valid and reliable. A total of 156 AYA survivors from three Canadian pediatric hospitals completed the scale. Regarding adult LTFU care, 68% of participants expected that the doctor will become like a friend, and 61% expected to spend a lot of time with the doctor during the appointment. Regarding the organization of their care, 87% expected to receive a reminder call before the appointment, while 88% expected to be called if they miss an appointment. Furthermore, 64% of survivors expected the doctor to look after all of their healthcare needs, not just those related to their prior cancer therapy. AYA childhood cancer survivors have specific beliefs/expectations about LTFU care, some of which may contrast with the reality of adult care services. Significant levels of unrealistic expectations may contribute to poor compliance with LTFU care. Prior to transfer, AYA survivors may benefit from preparation and education about the different culture of care that they will likely encounter in order to resolve dissonance and improve transition.
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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 | 0.005 |
| 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 | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".