Barriers and Facilitators of Transition from Pediatric to Adult Long-Term Follow-Up Care in Childhood Cancer Survivors
Bibliographic record
Abstract
PURPOSE: Despite the risk for late effects in adult survivors of cancer in childhood or adolescence, many survivors fail to transition from pediatric to adult long-term follow-up (LTFU) care. The purpose of this study was to identify the barriers and facilitators of transition from pediatric to adult LTFU care. METHODS: In this qualitative study, 38 Canadian survivors of cancer in childhood or adolescence, currently aged 15-26 years, were interviewed using semi-structured, open-ended questions. Participants belonged to one of four groups: pre-transition (n=10), successful transition (n=11), failed to transition (n=7), and transitioned to an adult center but then dropped out of adult care (n=10). A constructivist grounded theory approach was used to analyze the interview data. This approach consisted of coding transcripts line by line to develop categories and using constant comparison to examine relationships within and across codes and categories. Interviewing continued until saturation was reached. RESULTS: Three interrelated themes were identified that affected the transition process: micro-level patient factors (e.g., due diligence, anxiety), meso-level support factors (e.g., family, friends), and macro-level system factors (e.g., appointments, communication, healthcare providers). Factors could act as facilitators to transition (e.g., family support), barriers to transition (e.g., difficulty booking appointments), or as both a barrier and a facilitator (e.g., anxiety). CONCLUSION: This study illustrates the interaction between multiple factors that facilitate and/or prevent transition from pediatric to adult LTFU cancer care. A number of recommendations are presented to address potential macro-level system barriers to successful 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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".