Advance Care Planning in Oncology Nursing: An Interpretive Description Study
Bibliographic record
Abstract
AIM: To explore oncology nursing advance care planning practices and understand how to better support nurses in conducting advance care planning with patients and their families. DESIGN: Qualitative interpretive descriptive methodology. METHODS: Semi-structured, individual telephone or Zoom interviews with 19 oncology nurses in a Western province of Canada between May and August 2022. Interviews were audio-recorded, transcribed, de-identified, and analysed using inductive, thematic, and constant comparative techniques. RESULTS: Oncology nurses highlighted several factors affecting their ability to engage in advance care planning, including (1) uncertainties related to the nursing role in advance care planning, such as how and when a nurse ought to engage; (2) the educational, experiential, and training environment; and (3) structural barriers, such as a lack of time, space, and privacy; models of care that inhibit nurses from developing longitudinal relationships with their patients; and team dynamics that affect advance care planning interdisciplinary collaboration. CONCLUSION: To create environments that support oncology nurses to conduct advance care planning, the findings suggest uncertainties be addressed through a clear and cohesive organisational approach to advance care planning and ongoing, integrated educational opportunities. Further, service delivery models may need to be restructured such that nurses have dedicated time and space for nurse-led advance care planning and opportunities to develop trusting relationships with both patients and their interdisciplinary colleagues. IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE: Impact Oncology nurses recognised the value of advance care planning in supporting patient-centred care and shared decision making, yet they reported limited engagement in advance care planning in their practice. To support oncology nurses in conducting advance care planning, healthcare leaders may address (1) advance care planning-related uncertainties and (2) structural barriers that prevent nurses from engaging in advance care planning with patients and their families. Findings may guide modifications to care models, enhancing support for oncology nurses in conducting advance care planning. REPORTING METHOD: We selected and adhered to the Consolidated Criteria for Reporting Qualitative Research (COREQ) as the most applicable guideline. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".