12 - UNDERSTANDING PATIENT AND CAREGIVER EXPERIENCES OF ADVANCED CANCER CARE IN ALBERTA: A QUALITATIVE STUDY
Bibliographic record
Abstract
BackgroundPalliative care is an approach that improves the quality of life of patients and families facing challenges associated with life-threatening illness. In Alberta, most people who received palliative care received it late (within last 3 months of life), which has negative implications for patient and caregiver experiences, greater emotional distress, and decreased quality of life. This study aims to understand patient and caregiver experiences of advanced colorectal cancer care to inform development of an early palliative care pathway.MethodsQualitative study that is embedded within a larger program of research on implementation of Palliative Care Early and Systematic (PaCES). Semi-structured telephone interviews with patients living with advanced colorectal cancer and caregivers were conducted to explore their experiences with cancer care services received pre-intervention. Interview transcripts were thematically analyzed supported by the qualitative analysis software, NVivo.Results15 patients and 7 caregivers from Edmonton and Calgary were interviewed over the phone. A total of 6 main themes generated: 1. Meaning of Palliative Care; 2. Communication (subthemes: communication of diagnosis, communication between patient and oncologist, communication amongst providers); 3. Relationship with healthcare providers (including oncologist, family doctor, and nurses); 4. Access to care; 5. Patient readiness for advance care planning; 6. Patient and family engagement in care.Conclusion Most participants misperceived palliative care to mean u2018end of life careu2019, suggesting a need for improvement in the delivery of palliative care information to patients and caregivers. Understanding the care experiences of patients and caregivers will inform the development of a care pathway for early palliative care.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.013 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".