Experiences of cancer patients in palliative care with advanced care planning: A systematic review and meta-synthesis of qualitative studies
Bibliographic record
Abstract
PURPOSE: This systematic review and meta-synthesis aims to synthesize the perspectives and experiences of patients with advanced cancer of advanced care planning and advanced directives in a PC setting. METHODS: Qualitative studies published between 1991 and 2024 were included. A comprehensive search was performed across six electronic databases: CINAHL, Cochrane, OVID, PubMed, Scopus, and ScienceDirect. The Joanna Briggs Institute Critical Appraisal Checklist for Qualitative Research was applied for quality assessment. Thematic synthesis was applied to analyze data from 20 selected studies, involving 534 participants. RESULTS: Six key themes emerged: (1) Meaning of advanced care planning (ACP), (2) Initiating ACP, (3) Barriers and facilitators, (4) Communication in ACP, (5) Outcomes of ACP, and (6) Needs and wishes in ACP. Findings highlight ACP as a complex and dynamic process shaped by emotional, social, and institutional factors. While ACP promotes patient autonomy and reduces anxiety, reluctance, avoidance, and cultural barriers limit engagement. Effective clinician-patient communication, emotional readiness, and tailored interventions enhance ACP participation. CONCLUSIONS: Understanding the perspectives of advanced cancer patients is essential for improving ACP implementation in PC settings. Healthcare professionals must foster trust, provide culturally sensitive communication, and adapt ACP approaches to patients' evolving needs. Future research should focus on addressing emotional and systemic barriers to increase ACP participation and improve end-of-life care quality.
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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 | 0.046 | 0.123 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.010 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 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".