P-33 Characterising readiness for advance care planning (ACP): An interpretive descriptive study in supportive living
Bibliographic record
Abstract
<h3>Background</h3> Supportive living (SL), also known as assisted-living, residents are at risk of progressive cognitive decline and physical frailty, requiring treatment decisions. As such ACP is recommended but the factors associated with readiness to engage in ACP in SL are not fully understood. <h3>Aim</h3> The purpose of this study was to explore perceptions of readiness, barriers and facilitators to ACP of SL residents, their families and clinicians. <h3>Method</h3> This qualitative study utilised an Interpretive Descriptive (ID) approach. Participants were 9 residents from 3 SL facilities, 6 family members and 8 SL clinicians in a health region with an ACP policy and procedure. Data collection consisted of semi-structured interviews with participants. Interviews were coded, analysed and themes developed within each group. Themes were also compared across the groups to understand areas of convergence and distinctness. <h3>Results</h3> For SL residents, ACP is closely related to making the transition to SL rather than health decisions. Clinicians are either task oriented or conflicted regarding ACP implementation. Families of SL residents draw on personal experience as most have lost a relative or experienced prior decision making for a family member. Early analysis demonstrates the emergence of five themes across the groups: conceptualization of ACP, readiness for engagement, health uncertainty and difficulty in decision-making, barriers/facilitators. <h3>Discussion</h3> These findings will be used in a knowledge-to-action program to inform the clinical approach, resources and health region processes aimed at increasing readiness for ACP and ACP engagement by patients and families in SL.
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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 | 0.015 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.007 | 0.008 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| 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".