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Record W2810135760 · doi:10.1002/jts.22282

The Effect of Employment Status in Postdisaster Recovery: A Longitudinal Comparative Study Among Employed and Unemployed Affected Residents

2018· article· en· W2810135760 on OpenAlexaff
Mark Bosmans, Peter G. van der Velden

Bibliographic record

VenueJournal of Traumatic Stress · 2018
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsUniversity Health Network
Fundersnot available
KeywordsMental healthAnxietyDepression (economics)PopulationPsychiatryUnemploymentPsychologyAnxiety disorderOccupational safety and healthMedicineDemographyGerontologyEnvironmental health

Abstract

fetched live from OpenAlex

Population studies have shown that employed adults are healthier than unemployed adults. In this study, we examined whether this "healthy worker effect" is relevant in postdisaster mental health by examining whether trauma-exposed employed individuals have lower postdisaster initial mental health problems and/or whether they recover faster than trauma-exposed unemployed individuals. We compared the course of postevent intrusion and avoidance reactions, anxiety, depression, and sleeping difficulties of employed residents (n = 291) and unemployed residents (n = 269) affected by a fireworks disaster in a residential area of Enschede, The Netherlands. Measurements took place at 2-3 weeks (T1), 18 months (T2), and 4 years (T3) postdisaster. We used linear mixed-effect models to examine the course of mental health problems. Employment status was relevant, to a degree, in posttrauma recovery; although affected employed residents had significantly lower levels of mental health problems (initially and over time) than the unemployed, ds = 0.41-0.72, the recovery rate was the same for both groups. At T1 (neglecting the DSM 1-month criterion), T2, and T3, the prevalence of probable posttraumatic stress disorder was 45.4%, 18.9%, and 11%, respectively, among employed individuals, and 70.1%, 32.5%, and 30% among unemployed individuals. We concluded that research into the mental health of disaster victims should take employment status into account. Regarding postdisaster care, unemployed individuals may need special attention; although they may recover at the same rate as employed individuals, they suffer from more severe mental health problems, even years after the disaster.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.783

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.418
Teacher spread0.360 · 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

Citations20
Published2018
Admission routes1
Has abstractyes

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