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Record W2598703186 · doi:10.1002/jts.22173

Does the Vulnerability Paradox in PTSD Apply to Women and Men? An Exploratory Study

2017· article· en· W2598703186 on OpenAlexaboutno aff
Michel Dückers, Miranda Olff

Bibliographic record

VenueJournal of Traumatic Stress · 2017
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsnot available
Fundersnot available
KeywordsVulnerability (computing)Socioeconomic statusPsychologyDemographyPopulationClinical psychologySociology

Abstract

fetched live from OpenAlex

Recent research suggests that greater country vulnerability is associated with a decreased, rather than increased, risk of mental health problems. Because societal parameters may have gender‐specific implications, our objective was to explore whether the “vulnerability paradox” equally applies to women and men. Lifetime posttraumatic stress disorder (PTSD) prevalence data for women and men were retrieved from 11 population studies ( N = 57,031): conducted in Australia, Brazil, Canada, France, Lebanon, Mexico, Netherlands, Portugal, Sweden, Switzerland, and the United States. We tested statistical models with vulnerability, gender, and their interaction as predictors. The average lifetime PTSD prevalence in women was at least twice as high as it was in men and the vulnerability paradox existed in the prevalence data for women and men ( R 2 = .70). We could not confirm the possibility that gender effects are modified by socioeconomic and cultural country characteristics. Issues of methodology, language, and cultural validity complicate international comparisons. Nevertheless, this international sample points at a parallel paradox: The vulnerability paradox was confirmed for both women and men. The absence of a significant interaction between gender and country vulnerability implies that possible explanations for the paradox at the country‐level do not necessarily require gender‐driven distinction.

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)0.002
metaresearch head score (Gemma)0.000
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 score0.370
Threshold uncertainty score0.431

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.058
GPT teacher head0.387
Teacher spread0.329 · 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

Citations22
Published2017
Admission routes1
Has abstractyes

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