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Record W4386642822 · doi:10.54254/2753-7048/9/20230229

Causes and Recommendations of Stigma in PTSD

2023· article· en· W4386642822 on OpenAlexaff
Yi‐Ching Yang

Bibliographic record

VenueLecture Notes in Education Psychology and Public Media · 2023
Typearticle
Languageen
FieldPsychology
TopicPosttraumatic Stress Disorder Research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsStigma (botany)PsychologyMindfulnessClinical psychologyPosttraumatic stressSocial stigmaPsychiatryMental illnessSocial supportMental healthPsychotherapistMedicine

Abstract

fetched live from OpenAlex

In addition to suffering from symptoms, individuals with posttraumatic stress disorder (PTSD) also suffer from self-stigma and public stigmatization due to PTSD. This article examines the stigma that patients with PTSD usually experience, and whether these stigmas are related to the identity, economic status, and other co-occurring mental illnesses of patients. Through reviewing the previous studies, this paper discusses the causes, forms and effects of stigma. In addition, it was found that individualized psychotherapy programs and mindfulness can be effective in alleviating the stress of stigma for PTSD patients. And social acceptance and support for the PTSD community can be increased by managing content about the disorder on social media and changing the content framework of news organizations, such as increasing anti-stigma and introducing knowledge about PTSD. The social acceptance and support of the PTSD community can be increased by, for example, increasing anti-stigma and knowledge about PTSD. Future research should focus on addressing the stigma associated with mental illnesses such as PTSD and addressing the psychological damage caused by stigma.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.537
Threshold uncertainty score0.906

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.096
GPT teacher head0.453
Teacher spread0.357 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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