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Record W2883553866 · doi:10.3389/fpsyt.2018.00345

Prevalence Rates and Predictors of Generalized Anxiety Disorder Symptoms in Residents of Fort McMurray Six Months After a Wildfire

2018· article· en· W2883553866 on OpenAlexafffundabout
Vincent I. O. Agyapong, Marianne Hrabok, Michal Juhás, Joy Omeje, Edward Denga, Bernard Nwaka, Idowu Akinjise, Sandra E. Corbett, Shahram Moosavi, Matthew Brown, Pierre Chue, Andrew J. Greenshaw, Xin‐Min Li

Bibliographic record

VenueFrontiers in Psychiatry · 2018
Typearticle
Languageen
FieldPsychology
TopicPosttraumatic Stress Disorder Research
Canadian institutionsUniversity of AlbertaAlberta Health Services
FundersAlberta InnovatesKillam TrustsUniversity of Alberta
KeywordsGeneralized anxiety disorderAnxietyPsychiatryAnxiety disorderGeneralized anxietyMental healthClinical psychologyPsychologyMedicineDemography

Abstract

fetched live from OpenAlex

The Fort McMurray wildfire was the costliest disaster in Canadian history, with far-reaching impacts. The purpose of this paper is to examine the prevalence and risk factors of elevated generalized anxiety disorder (GAD) symptomatology in residents of Fort McMurray 6 months after the wildfire. Data were collected via random selection procedures from 486 participants. Generalized anxiety disorder symptoms were measured via the GAD-7. The 1-month prevalence rate for GAD symptomatology 6 months after the disaster was 19.8% overall, regression analyses revealed six variables with significant unique contributions to prediction of GAD symptomatology. Significant predictors were: pre-existing anxiety disorder, witnessing of homes being destroyed by the wildfire, living in a different home after the wildfire, receiving limited governmental support or limited family support, and receiving counseling after the wildfire. Participants with these risk factors were between two to nearly seven times more likely to present with GAD symptomatology. In addition, participants who presented with elevated symptomatology were more likely to increase use or problematically use substances post-disaster. This study extends the literature on mental health conditions and risk factors following disasters, specifically in the area of generalized anxiety. Findings and implications are discussed.

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)0.000
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 score0.018
Threshold uncertainty score0.934

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.009
GPT teacher head0.308
Teacher spread0.298 · 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

Citations88
Published2018
Admission routes3
Has abstractyes

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