Virtual, Nurse-Led Early Primary Palliative Care Intervention (ELICIT) for Community-Dwelling Older Adults With Cognitive Impairment: Protocol for a Randomized Controlled Trial
Bibliographic record
Abstract
Background: Although dementia is a serious illness that progresses over many years, little is known about the primary palliative care needs of individuals who have it, especially those living in the community. Objective: This trial aims to test the impact of a virtual, nurse-led early primary palliative care intervention (ELICIT) on older adults living in the community who are chronically ill and have a diagnosis of cognitive impairment or are at risk of it. Methods: A total of 200 community-dwelling older adults who were chronically ill and had varying degrees of cognitive impairment were recruited and randomized to either usual care or usual care + a virtual, nurse-led ELICIT. For both arms, we will track the number of participants who (1) report supportive care needs to the blinded evaluators and (2) complete conversations on goals of care and document advance directives and the Physician Orders for Life-Sustaining Treatment form in the electronic health record. We will also track their end-of-life resource use and the percentage of participants who receive goal-concordant care. Changes in Edmonton Symptom Assessment Scale, Patient Activation Measure, and Quality of Life in Alzheimer's Disease scores will be tracked and analyzed. Results: As of October 2025, we have recruited 200 participants. We are following all study participants on an ongoing basis to determine whether they received goal-concordant care at the end of life and their resource use patterns. We hypothesize that, compared to the usual care arm, more participants in the intervention arm will (1) express supportive care needs to the blinded evaluators, (2) complete goals of care conversations, document advance care planning, and (3) have higher levels of goal-concordant care and lower end-of-life resource use. Conclusions: The identification of the primary palliative care needs of community-dwelling older adults who are chronically ill and have various levels of cognitive impairment will help refine the intervention and enable trained nurses to provide virtual early primary palliative care within the scope of nursing.
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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 | 0.025 | 0.024 |
| Meta-epidemiology (narrow) | 0.007 | 0.003 |
| Meta-epidemiology (broad) | 0.013 | 0.006 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.070 | 0.011 |
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".