Advance care planning in community dwellers: A constructivist grounded theory study of values, preferences and conflicts
Bibliographic record
Abstract
Background: Most laypeople have not engaged in any advance care planning. Yet they are expected to articulate choices for life-sustaining interventions when they need admission to an acute care hospital in Canada. Aim: To describe how laypeople understand and make decisions for life-sustaining interventions when engaging in advance care planning. Design: Semi-structured interviews using constructivist grounded theory methodology and purposive sampling. Setting: Mid-size Canadian urban community Participants: In total, 20 healthy laypeople, 55 years and older, participated in in-depth semi-structured face-to-face interviews. Theoretical sampling was used to explore findings from the first round of interviews. Ten participants were invited for repeat interviews. Results: Four major themes were identified. Most participants claimed at the outset that they had engaged in advance care planning, but they were unfamiliar with contemporary life-sustaining interventions and had not factored these into their decisions. Participants’ confidence in their substitute decision makers precluded them from having explicit discussions with these individuals. Participants expressed their values and preferences in terms of unacceptable functional outcomes from serious illness, rather than desired interventions. The process of articulating their preferences within the interviews was subject to decision conflicts, which in turn helped them re-evaluate and refine their decisions. Conclusion: Advance care planning for the healthy older adult is challenging. Meaningful engagement may lead to conflicts in decision-making. Efforts to improve engagement must reflect what patients know and understand, their focus on unacceptable negative outcomes rather than interventions, and the need for iterative discussions with health-care providers.
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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 | 0.028 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.017 | 0.019 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 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".