Examining the Knowledge, Awareness, and Perceptions of Palliative Care in the General Public Over Time: A Scoping Literature Review
Bibliographic record
Abstract
BACKGROUND: The field of palliative care (PC) is growing as the world population ages and burden of chronic diseases increases. Thus, it is important that the general public is knowledgeable about PC and the benefits PC provides. OBJECTIVE: The aim of this study is to describe the public's knowledge, awareness, and perceptions of PC and determine whether these have changed over time. METHODS: A scoping literature review was conducted from 1968 to May 2019 using PubMed, EMBASE, and MEDLINE databases. RESULTS: Thirteen studies met inclusion criteria that originated from the United States, Canada, Scotland, Italy, New Zealand, Ireland, United Kingdom, Korea, and Sweden between years 2003 and 2019. Participants were adults and mostly younger than 64 years, women, and Caucasian. The majority of studies reported the public having poor knowledge (7/9 articles) and awareness (4/6 articles) of PC over the past 16 years. Top characteristics associated with increased levels of knowledge and/or awareness of PC included women (6/8 articles), age 40+ (6/8 articles), experience with a close friend and/or relative requiring PC (4/8 articles), and working in health-care and/or PC (4/8 articles). The most common perceptions of PC were associated with patients who have terminal illnesses and end-of-life care. Participants commonly received information about PC from the media, having a close friend or relative requiring PC, and working in a health-care setting. CONCLUSIONS: The public has poor knowledge and awareness about PC and several misperceptions exist. These findings have remained constant over time despite growth in the field of PC, which highlights the strong need for focused educational interventions.
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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 | 0.019 | 0.092 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.024 | 0.023 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 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".