Evidence map›Paper›PMID 41607925›Full record

ArticleFrontiers in public health2025

Analysis of middle-aged and older adults' willingness concerning living wills and associated factors.

Linyu Jiang, Yuwan Duan, Daping Li

Abstract read
In one paragraph

Article in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
–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

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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

3 authors.

Linyu JiangSchool of Public Health, Guangdong Medical University, Dongguan, Guangdong, China.
Yuwan DuanSchool of Public Health, Guangdong Medical University, Dongguan, Guangdong, China.
Daping LiSchool of Public Health, Guangdong Medical University, Dongguan, Guangdong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To investigate the current status of Living Will willingness among middle-aged and older adults in Shenzhen, China, and to systematically identify its associated influencing factors. Methods: Based on the Theory of Planned Behavior and the Life Course Theory, a cross-sectional survey was conducted from May 2023 to February 2024. A total of 519 middle-aged and older adults were recruited in Shenzhen. Data were collected using a general information questionnaire, a Living Will knowledge questionnaire, a Living Will attitude scale, a family APGAR scale, a health status scale, and a social support scale. Chi-square test, Mann-Whitney U test, and Firth penalized logistic regression analysis were employed to identify associated factors. Results: The proportion of participants with a positive willingness toward creating a Living Will was 64.7%. Significant influencing factors included age ( Conclusion: Middle-aged and older adults in Shenzhen demonstrated a relatively positive willingness regarding Living Wills. Nine protective factors were identified, including a higher education level, presence of religious belief, higher monthly income, experience of witnessing medical rescue or death, better knowledge of Living Wills, a positive attitude toward Living Wills, good family function and psychological status, and strong social support.

Indexed as

Living WillsAgedChinaCross-Sectional StudiesFemaleHumansMaleMiddle AgedSocial SupportSurveys and Questionnairesassociated factorscross-sectional studyFirth’s penalized logistic regression analysisliving willwillingness

Identifiers

PMID41607925
PMCPMC12834717

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.