Evidence map›Paper›PMID 35463662›Full record

ArticleJournal of healthcare engineering2022

Evaluating Organ Donation Decision in ICU Patients' Families by Analytic Network Process Approach.

Chia-Lun Lo, Hsiao-Yun Chang, Guang-Mao Lee

Abstract read
In one paragraph

Article in Journal of healthcare engineering, 2022. 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

3 authors.

Chia-Lun LoDepartment of Health-Business Administration, Fooyin University, Kaohsiung City 83102, Taiwan.ORCID 0000-0002-8204-3471
Hsiao-Yun ChangDepartment of Nursing, Chang Gung University of Science and Technology, Taoyuan City 33303, Taiwan.ORCID 0000-0003-0877-3289
Guang-Mao LeeDepartment of Nursing, Kaohsiung Municipal United Hospital, Kaohsiung City 80457, Taiwan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The imbalance between supply and demand for organs has been a global crisis, despite the efforts of transplant coordinators from healthcare institutions to promote donor registration. Because the patient's family has legal rights over the patient's remains, they can easily undermine any efforts spent on organ procurement by simply refusing the patient's consent before death in practice. Most related studies seldom mention the decision-making on organ donation from patients' families. The objectives of this study are to find what are the priorities of those factors acting as the pillars of organ donation by patients' families. This study applied the analytic network process (ANP) to the prioritization factors contributing toward the willingness of families to donate organs of intensive care unit patients. The purposive sampling method used structured questionnaires and ANP questionnaires to enroll 180 patients' families from five intensive care units who met the criteria in the regional teaching hospital of southern Taiwan. Through the ANP analysis, it was found that when family members made organ donation decisions, the weights of the four domains are as follows: psychology-47.6%, externality-20.3%, spirituality-19.7%, and physiology-12.3%. The main decision-making factors that influenced the weighting factors were "attitude" (31.5%), "physician's experience" (0.88%), "religion" (19.3%), and "organ selection" (31.9%). These results could assist organ donation teams to take the best strategies for persuading people to agree with organ donation and formulating an individual organ donation plan.

Indexed as

Decision MakingTissue and Organ ProcurementTissue DonorsFamilyHumansIntensive Care Units

Identifiers

PMID35463662
PMCPMC9033390

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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.