Healing relationships between patients from visible minority groups and their clinicians in palliative care: Protocol for an interpretive description study
Bibliographic record
Abstract
Background: Palliative care supports human dignity across the trajectory of a serious illness. In addition to addressing multiple dimensions of suffering among patients, palliative care aims to foster healing-a relational process through which one experiences personal growth and transcendence. Palliative care clinicians build relationships with patients through communication practices that enhance trust and other relational elements. These relationships hold the potential to mitigate patient suffering. However, patients from visible minority groups may face structural barriers and clinician biases that impede the formation of healing-oriented relationships. We know little about their experiences of relationships in this setting. Objectives: To examine the qualities of healing clinician-patient relationships from the perspective of visible minority patients receiving outpatient palliative care. Design: Interpretive description. Methods and analysis: We will recruit 10-15 patients who identify themselves as being part of a visible minority group and have had at least two outpatient palliative care visits. We will conduct semi-structured in-depth individual interviews and analyze these based on deductive-inductive thematic analysis initially grounded in current evidence. We will identify relational elements that patients value and that promote positive connections with clinicians. We will produce a rich description of "healing" and understand the role of relationships in healing. Ethics: We have obtained institutional ethics board approval to conduct this study. Discussion: Relationships may alleviate patient suffering and promote healing even in settings of serious illness. Clinicians should attend to nurturing meaningful relationships with patients from visible minority groups who face additional challenges beyond those brought by a serious illness. Our findings may inform clinical training programs that promote relationship-building behaviors. Efforts to promote higher quality relationships with these patient groups may improve their overall quality of care and address inequities in palliative care.
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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 | 0.073 | 0.076 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.047 | 0.010 |
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".