QLTI-14. Enhancing Awareness and Use of Support Services for Adolescents and Young Adults with High-Grade Glioma: Evaluating 1-Minute Videos and Centralized Resource Navigator
Bibliographic record
Abstract
Abstract BACKGROUND Adolescents and young adults (AYAs) diagnosed with high-grade glioma (HGG) experience profound disruptions in education, employment, relationships, and identity during a pivotal stage of life. Previous work has revealed substantial gaps in their awareness of and access to essential supportive resources. This study aimed to evaluate the effectiveness of a co-developed educational 1-minute videos and centralized online resource navigator in improving knowledge, accessibility and use of age- and disease-specific support services. METHODS A mixed-methods study design was implemented across four Ontario cancer centres: Princess Margaret, Sunnybrook Odette, Juravinski, and Verspeeten Family Cancer Centre. Participants completed pre- and post-intervention surveys measuring awareness, confidence in navigating services, and unmet needs. Focus groups were conducted to explore perceptions of the tools, and transcripts were analyzed thematically using Braun and Clarke’s framework. In parallel, an environmental scan of 22 major Canadian cancer centres assessed national disparities in AYA HGG support availability. RESULTS Preliminary findings suggest increased participant awareness and engagement with HGG-specific support resources following exposure to the 1-minute educational videos and resource navigator. Early feedback indicates that both tools are viewed as accessible, age-appropriate, and relevant. Participants have expressed appreciation for centralized guidance in navigating complex systems of care. Final results will provide a more robust understanding of changes in awareness, confidence, and perceived gaps post-intervention. CONCLUSION The 1-minute educational videos and resource navigator are effective, scalable tools that address critical awareness gaps for AYA HGG patients. These interventions reflect a patient-centered model and provide a framework for national standardization of AYA cancer support services. Future work will expand these tools to other AYA cancer populations and integrate them into clinical care pathways across Canada.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".