Adapting the Voicing My CHOiCES Advance Care Planning Communication Guide for Australian Adolescents and Young Adults with Cancer: Appropriateness, Acceptability, and Considerations for Clinical Practice
Bibliographic record
Abstract
Background: Adolescents and young adults (AYAs) with life-threatening illnesses need support to discuss and voice their end-of-life choices. Voicing My CHOiCES (VMC) is a research-informed American advanced care planning guide designed to help facilitate these difficult discussions. This multi-perspective study aimed to evaluate its appropriateness, acceptability, and clinical considerations for Australian AYAs with cancer. Procedure: Forty-three participants including AYAs who were either undergoing or recently completed cancer treatment, their parents, and multidisciplinary health professionals assessed the acceptability of each VMC section quantitatively (appropriateness—yes/no, helpfulness and whether content caused stress—1 = not at all, to 5 = very) and qualitatively (sources of stress). AYAs also assessed the benefit and burden of completing several sections of the document, to inform clinical considerations. We conducted a mixed-methods analysis to obtain descriptive statistics and to identify prominent themes. Results: In terms of acceptability, almost all participants (96%) rated VMC as appropriate overall. Perceived helpfulness to their situation (to themselves/their child/their patients), to others, and stressfulness were rated, on average, as 4.1, 4.0, and 2.7/5, respectively. Stress was attributed to individual and personal factors, as well as interpersonal worries. All sections were considered more beneficial than burdensome, except for the Spiritual Thoughts section (Section 6). Conclusions: While VMC is an acceptable advance care planning guide for AYAs with cancer, changes to the guide were suggested for the Australian context. Health professionals implementing VMC will need to address and mitigate anticipated sources of stress identified here. Future research evaluating the impact of a new culturally adapted Australian VMC guide is an important next step. Finally, the clinical implications of the present study are suggested.
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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 | 0.021 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 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".