DISP-05. UNDERSTANDING THE INDIVIDUAL CHALLENGES AND EXPERIENCES OF YOUNG ADULTS WITH A DIAGNOSIS OF GLIOBLASTOMA AND HIGH-GRADE ASTROCYTOMA
Bibliographic record
Abstract
Abstract High-grade gliomas are highly aggressive and fatal primary malignant brain tumors in adults with ineffective existing treatment methods. Older adults are greatly impacted by high-grade gliomas as they are more common among this population. Young adults (individuals aged 18-39) are uniquely impacted by high-grade glioma. However, there are few resources and information available to address these unique needs. The purpose of this study is to explore the lived experience of this population to inform the development of resources to help address their specific needs. A qualitative descriptive design drawing on thematic analysis was chosen to conduct and analyze interviews with young adult high-grade glioma patients at the Princess Margaret Cancer Center. Interviews focused on patient experiences as a high-grade glioma patient at Princess Margaret Cancer Center, the challenges they face and changes they would like implemented. A coding framework was created to determine emerging themes using qualitative data analysis software NVivo 10. To date, 5 interviews (1 men; 4 women; age range 19-37) have been completed. Interviews described the challenges living with high-grade glioma as a young adult and the changes in resources and support services patients would like implemented. Experiences highlighted 1) difficulty accepting this change in life and disruptions brought upon life goals and plans at the young adult age; 2) an overall lack of young adult high-grade glioma specific education, advocacy and support resources 3) A call for more community building and connecting so patients do not feel alone through this diagnosis. These patient interviews highlight a connection between the young adult age and high-grade glioma diagnosis and the challenges experienced and the services required. These results will serve as the foundation to advocate for the creation of tools that cater to patient needs of young adult high-grade glioma patients.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".