Understanding Advance Care Planning in Patients and Care Partners Living with Parkinson’s disease
Bibliographic record
Abstract
Project Summary Objective: Advance care planning (ACP) is a core quality measure in caring for individuals with Parkinson disease (PD) and there are no best practice standards for how to incorporate ACP into PD care. This study describes patient and care partner perspectives on ACP to inform a patient- and care partner-centered framework for clinical care. Methods: This is a qualitative descriptive study of 30 patients with PD and 30 care partners within a multisite, randomized clinical trial of neuropalliative care compared to standard care. Participants were individually interviewed about perspectives on ACP, including prior and current experiences, barriers to ACP, and suggestions for integration into care. Interviews were analyzed using theme analysis to identify key themes. Data Overview Sixty-seven interview transcripts from 60 participants including individuals with Parkinson Disease (n=30) or care partners of individuals with PD (n=30). Interviews were conducted at the 12-month follow up after Dr. Benzi Kluger's PCORI-funded three-site RCT of outpatient palliative care compared to usual care. Interviews specifically probed on patient-care-partner-palliative care/usual neurological care communication and advance care planning. Three sites are: University of California San Francisco (UCSF); University of Alberta (Alberta); University of Colorado Denver/Anschutz Medical Campus (UCD) Interviews were conducted by trained qualitative research assistants (not involved in the intervention) between September 2017 and March 2018. During this period, 137 participants (81 patients and 56 care partners) had reached the 12-month visit. The study planned a goal of 60 interviews to allow sufficient opportunity to sample across trial sites and across participant type (patient or care partner). Patients and care partners were purposefully selected for interviews from each site, study arm, and sex to ensure representation across these populations. Other efforts to maximize the variance in the sample included specifically including individuals with cognitive impairment, high disease severity (based on Hoehn & Yahr score), or lacking a care partner. All participants, whether a patient or care partner, were interviewed separately. In some cases, multiple interviews were conducted due to a) participant preference, or b) additional probing related to advance care planning or other palliative care topics.
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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) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".