CanPROS Scientific Conference 2019 Poster Abstracts
Bibliographic record
Abstract
Background: Palliative care is an approach that improves quality of life for patients and families facing challenges associated with life-threatening illness. In Alberta, most people who received palliative care received it late. Late palliative care negatively affects patient and caregiver experiences and decreases quality of life. This study aims to understand patient and caregiver experiences of advanced colorectal cancer care to inform an early palliative care pathway for advanced cancer care. Methods: A qualitative study that is embedded within a larger program of research on the implementation of the Palliative Care Early and Systematic (paces) pathway. Semi-structured telephone interviews with patients and their caregivers living with advanced colorectal cancer were conducted to explore their experiences with cancer care services received before pathway implementation. Interviews were transcribed, and the data were thematically analyzed, supported by the qualitative analysis software NVivo. Results: Interviews with 15 patients and 7 caregivers from Edmonton and Calgary were conducted over the telephone. Most participants found the Putting Patients First tool to be useful at their appointments; however, some mentioned a preference for viewing their scores over time. A total of 6 main themes were identified: (1) Meaning of palliative care (2) Communication (3 main subthemes: communication of diagnosis, communication between patient and oncologist, communication between providers) (3) Relationship with health care providers (including oncologist, family doctor, and nurses) (4) Access to care (cost of care, proximity to care, after hours care) (5) Patient readiness for advance care planning (6) Patient and family engagement in care, with mixed experiences in how patients were involved in their care. Conclusions: Most participants misperceived palliative care to mean “end-of-life care,” suggesting a need for improvement in the delivery of palliative care information. 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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.682 | 0.448 |
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".