Evidence map›Paper›PMID 41056296›Full record

ArticlePloS one2025

Nurses' high valuation of palliative care versus patient and family misconceptions: A mixed-approach study of Advanced Care Planning implementation in China.

Chenyan Liang, Suzhen Lv, Jia Song, Leiwen Tang

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Chenyan LiangDepartment of Nursing, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, People's Republic of China.
Suzhen LvDepartment of Rheumatology and Immunology, Lishui Central Hospital, Lishui, Zhejiang, China.
Jia SongDepartment of Rheumatology and Immunology, Lishui Central Hospital, Lishui, Zhejiang, China.
Leiwen TangDepartment of Nursing, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo assess the implementation and barriers of Advance Care Planning (ACP) from the perspectives of nurses, patients, and family members in a Chinese healthcare setting, providing evidence for targeted interventions to enhance ACP awareness.

methodsA mixed-methods design combined a cross-sectional survey and qualitative interviews. Questionnaires measured ACP-related knowledge, attitudes, practices (KAP), and perceived barriers among 843 nurses, 384 patients, and 857 family members. Based on responses, 15 patients and 20 family members with negative views on ACP were invited for semi-structured interviews and focus groups.

findingsNurses rated ACP as highly important and reported effective palliative care practices, while patients and families showed substantial cognitive gaps. Over 90% of patients valued ACP, but only ~30% believed it was well implemented; many families associated it with treatment abandonment. Multivariable analysis identified hospital type, clinical experience, and information sources as KAP predictors. Qualitative results linked misconceptions to poor communication and insufficient public education.

conclusionNurses endorse ACP, but patients and families often misinterpret it as giving up treatment. Improved communication and tailored education are critical to increasing ACP acceptance in China.

Indexed as

Advance Care PlanningFamilyNursesPalliative CareAdultAgedAttitude of Health PersonnelChinaCross-Sectional StudiesFemaleHealth Knowledge, Attitudes, PracticeHumansMaleMiddle AgedSurveys and Questionnaires

Identifiers

PMID41056296
PMCPMC12503265

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.