Evidence map›Paper›PMID 39297225›Full record

ArticleEuropean psychiatry : the journal of the Association of European Psychiatrists2024

Understanding mental health help-seeking and stigma among Hungarian adults: A network perspective.

Valerie S Swisher, Dorottya Őri, Zoltán Rihmer, Róbert Wernigg

Abstract read
In one paragraph

Article in European psychiatry : the journal of the Association of European Psychiatrists, 2024. 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

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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

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3 · Its place in the literature

Who cites it

3 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

4 authors.

Valerie S SwisherThe Pennsylvania State University, State College, University Park, PA, USA.ORCID 0000-0002-9311-9785
Dorottya ŐriInstitute of Behavioural Sciences, Semmelweis University, Budapest, Hungary.ORCID 0000-0003-0878-165X
Zoltán RihmerDepartment of Psychiatry and Psychotherapy, Semmelweis University, Budapest, Hungary.
Róbert WerniggNational Directorate-General for Hospitals, Budapest, Hungary.ORCID 0000-0001-5157-5902

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHungarians exhibit more negative attitudes toward help-seeking for mental health problems compared to other European countries. However, research on help-seeking in Hungary is limited, and it is unclear how stigma relates to help-seeking when considering demographic and clinical characteristics. We used a network analytic approach to simulate a stigma model using hypothesized constructs in a sizable sample of Hungarian adults.

methodsParticipants were 345 adults recruited from nine primary care offices across Hungary. Participants completed self-report measures assessing public stigma, self-stigma, experiential avoidance (EA), attitudes toward seeking professional psychological help, anxiety, depression, demographics, prior use of mental health services, and whether they have a family member or friend with a mental health condition.

resultsEA and anxiety were the most central nodes in the network. The network also revealed associations between greater EA with greater public stigma, anxiety, depression, and having a family member or friend with a mental health condition. More positive attitudes toward seeking help were associated with lower self-stigma, public stigma, and having received psychological treatment in their lifetime. Being female was associated with lower income, higher education, and having received psychological treatment in their lifetime. Finally, having a family member or friend with a mental health condition was associated with having received psychological treatment in their lifetime and greater public stigma.

conclusionsThe strength centrality and associations of EA with clinical covariates and public stigma implicate its importance in stigma models. Findings also suggest that while some aspects of existing stigma models are retained in countries like Hungary, other aspects may diverge.

Indexed as

Mental Health ServicesPatient Acceptance of Health CareSocial StigmaAdultAnxietyFemaleHelp-Seeking BehaviorHumansHungaryMaleMental DisordersMiddle Agedexperiential avoidancehelp-seeking behaviorHungarynetwork analysispublic stigmaself-stigma

Identifiers

PMID39297225
PMCPMC11457119

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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.