Young Adults’ Perceptions of the Venturing Out Pack Program as a Tangible Cancer Support Service
Bibliographic record
Abstract
PURPOSE/OBJECTIVES: To explore the extent to which contents contained in a backpack called the Venturing Out Pack (Vo-Pak) assist in meeting the practical, psychosocial, and informational needs of young adults (YAs), as well as how the Vo-Pak could better meet the needs of YAs. . RESEARCH APPROACH: Qualitative, descriptive. . SETTING: A university-affiliated adult hospital cancer center in Montreal, Quebec. . PARTICIPANTS: 12 YAs treated for cancer. . METHODOLOGIC APPROACH: One-time, individual, semistructured interviews. Verbatim transcripts underwent thematic analysis. . FINDINGS: Participants viewed the Vo-Pak as a welcoming, ready-to-use, timely package that met many cancer-related needs. The Vo-Pak contains three kits. CONCLUSIONS: This program adds value to efforts to enhance cancer care for YAs. Integrating participants' recommendations contributes to the overarching goal of comprehensive person-centered care to an underserved segment of the cancer population. . INTERPRETATION: The Vo-Pak program could be optimized by re-engaging healthcare professionals in its broader dissemination. Champions may be added to optimize the successful implementation of tangible support programs. YAs seem eager to connect with peers. The Vo-Pak can be instrumental in facilitating these connections and enabling these exchanges.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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".