Family caregivers of Palliative Cancer Patients at Home: The puzzle of Pain Management
Bibliographic record
Abstract
The purpose of this grounded theory study was to understand the processes used by family caregivers to manage the pain of cancer patients at home. A total of 24 family caregivers participated. They were recruited using purposeful then theoretical sampling. The data sources were taped, transcribed (semi-structured) interviews and field notes. Data analysis was based on Strauss and Corbin's (1998) requirements for open, axial, and selective coding. The result was an explanatory model titled "the puzzle of pain management," which includes four main processes: "drawing on past experiences"; "strategizing a game plan"; "striving to respond to pain"; and "gauging the best fit," a decision-making process that joins the puzzle pieces. Understanding how family caregivers assemble their puzzle pieces can help health care professionals make decisions related to the care plans they create for pain control and help them to recognize the importance of providing information as part of resolving the puzzle of pain management.
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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 | 0.011 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".