Palliative Care and Parkinson's Disease: Caregiver Perspectives
Bibliographic record
Abstract
BACKGROUND: Palliative care for Parkinson's disease (PD) is an emerging area of interest for clinicians, patients and families. Identifying the palliative care needs of caregivers is central to developing and implementing palliative services for families affected by PD. The objective of this paper was to elicit PD caregiver needs, salient concerns, and preferences for care using a palliative care framework. MATERIALS AND METHODS: 11 PD caregivers and one non-overlapping focus group (n = 4) recruited from an academic medical center and community support groups participated in qualitative semi-structured interviews. Interviews and focus group discussion were digitally recorded, transcribed and entered into ATLAS.ti for coding and analysis. We used inductive qualitative data analysis techniques to interpret responses. RESULTS: Caregivers desired access to emotional support and education regarding the course of PD, how to handle emergent situations (e.g. falls and psychosis) and medications. Participants discussed the immediate impact of motor and non-motor symptoms as well as concerns about the future, including: finances, living situation, and caretaking challenges in advanced disease. Caregivers commented on the impact of PD on their social life and communication issues between themselves and patient. All participants expressed interest and openness to multidisciplinary approaches for addressing these needs. CONCLUSIONS: Caregivers of PD patients have considerable needs that may be met through a palliative care approach. Caregivers were receptive to the idea of multidisciplinary care in order to meet these needs. Future research efforts are needed to develop and test the clinical and cost effectiveness of palliative services for PD caregivers.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.004 |
| 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".