Evidence map›Paper›PMID 36982083›Full record

ArticleInternational journal of environmental research and public health2023

Near-Suicide Phenomenon: An Investigation into the Psychology of Patients with Serious Illnesses Withdrawing from Treatment.

Quan-Hoang Vuong, Tam-Tri Le, Ruining Jin, Quy Van Khuc, Hong-Son Nguyen, Thu-Trang Vuong, Minh-Hoang Nguyen

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Article in International journal of environmental research and public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

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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

7 authors.

Quan-Hoang VuongCentre for Interdisciplinary Social Research, Phenikaa University, Hanoi 100803, Vietnam.ORCID 0000-0003-0790-1576
Tam-Tri LeCentre for Interdisciplinary Social Research, Phenikaa University, Hanoi 100803, Vietnam.ORCID 0000-0003-3384-4827
Ruining JinCivil, Commercial and Economic Law School, China University of Political Science and Law, Beijing 100088, China.ORCID 0000-0002-8542-7614
Quy Van KhucFaculty of Development Economics, VNU University of Economics and Business, Vietnam National University, Hanoi 100000, Vietnam.ORCID 0000-0001-9516-2413
Hong-Son NguyenOffice of CPV Central Committee, 1A Hung Vuong, Hanoi 100000, Vietnam.
Thu-Trang VuongSciences Po Paris, 75007 Paris, France.ORCID 0000-0002-7262-9671
Minh-Hoang NguyenCentre for Interdisciplinary Social Research, Phenikaa University, Hanoi 100803, Vietnam.ORCID 0000-0002-7520-3844

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Patients with serious illnesses or injuries may decide to quit their medical treatment if they think paying the fees will put their families into destitution. Without treatment, it is likely that fatal outcomes will soon follow. We call this phenomenon "near-suicide". This study attempted to explore this phenomenon by examining how the seriousness of the patient's illness or injury and the subjective evaluation of the patient's and family's financial situation after paying treatment fees affect the final decision on the treatment process. Bayesian Mindsponge Framework (BMF) analytics were employed to analyze a dataset of 1042 Vietnamese patients. We found that the more serious the illnesses or injuries of patients were, the more likely they were to choose to quit treatment if they perceived that paying the treatment fees heavily affected their families' financial status. Particularly, only one in four patients with the most serious health issues who thought that continuing the treatment would push themselves and their families into destitution would decide to continue the treatment. Considering the information-filtering mechanism using subjective cost-benefit judgments, these patients likely chose the financial well-being and future of their family members over their individual suffering and inevitable death. Our study also demonstrates that mindsponge-based reasoning and BMF analytics can be effective in designing and processing health data for studying extreme psychosocial phenomena. Moreover, we suggest that policymakers implement and adjust their policies (e.g., health insurance) following scientific evidence to mitigate patients' likelihood of making "near-suicide" decisions and improve social equality in the healthcare system.

Indexed as

SuicideBayes TheoremFamilyHumansInsurance, HealthPatientsBMF analyticsfinancial burdenmindsponge theorynear-suicidepatients

Identifiers

PMID36982083
PMCPMC10049730

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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.