Patient-Centered Care for Adolescents and Young Adults with an Uncertain or Poor Cancer Prognosis: A Secondary Analysis of What Is Needed According to Patients, Caregivers, and Healthcare Providers
Bibliographic record
Abstract
Patient-centered care focuses on aligning healthcare with a person's values and preferences to support their health and life goals. This approach is especially crucial among adolescents and young adults (AYAs-with a primary cancer diagnosis between the ages of 18 and 39) facing an uncertain or poor cancer prognosis (UPCP), whose care needs differ from those undergoing curative treatment. This study aims to gain insights from AYAs with a UPCP, their informal caregivers, and healthcare professionals (HCPs) to define optimal patient-centered care and identify barriers to its implementation. We conducted semi-structured interviews with 46 AYAs, 39 informal caregivers, and 49 HCPs from various clinical backgrounds. Findings highlighted the need of AYAs for an equal relationship with HCPs and active involvement in decision-making, alongside tailored information addressing their unique challenges. Informal caregivers expressed the need for information to support patients while preferring a minimal focus on themselves. HCPs noted the necessity for specialized training to meet the specific needs of AYAs with a UPCP, reporting difficulties in providing tailored support due to the disease's uncertainties. This study's results can lead to improved healthcare for this population and enhance educational modules for HCPs, equipping them to better support AYAs facing a UPCP.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".