Navigating choice: eating, drinking and decision-making at end of life for individuals with cognitive impairment
Bibliographic record
Abstract
Current clinical guidelines offer limited direction for speech-language pathologists (SLPs) supporting eating and drinking decisions in palliative care (PC), particularly for individuals with dysphagia and co-occurring cognitive impairment. This population presents unique clinical, ethical and interpersonal challenges that often fall outside existing frameworks such as ‘Eating and Drinking with Acknowledged Risk’. This scoping review explores the key considerations for SLPs involved in end-of-life decision-making in these complex cases. A qualitative scoping review was conducted and analysed thematically. Twenty-seven articles met inclusion criteria, from which six overarching themes were identified: person-centred care; emotional and relational dynamics; ethical decision-making complexity; medical risk; barriers to effective clinical practice; and legal considerations. Findings reveal inconsistencies in practice and limited guidance for SLPs navigating care for individuals with cognitive impairment at the end of life. The review highlights a pressing need for evidence-informed frameworks to support ethical, person-centred care and calls for improved interdisciplinary collaboration and greater emphasis on autonomy and quality of life in this underrepresented area and population of practice.
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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 | 0.022 | 0.078 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| 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".