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Individual Predictors of Traumatic Reactions in Firefighters

2000· article· en· W2064129036 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Journal of Nervous and Mental Disease · 2000
Typearticle
Languageen
FieldPsychology
TopicPosttraumatic Stress Disorder Research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPsychologyPsychological resilienceDistressClinical psychologyAlienationStressorFeelingInterpersonal communicationLocus of controlSocial supportVulnerability (computing)Depression (economics)Intervention (counseling)Developmental psychologySocial psychologyPsychiatry

Abstract

fetched live from OpenAlex

Increasingly, theorists and researchers in the area of trauma are pointing to the importance of individual differences in resilience and vulnerability as key determinants of the intensity and duration of trauma-related symptoms. Determining the relative influence of individual predictors is important for the further development of theoretical models for understanding trauma responses and for the subsequent development of intervention strategies that are sensitive to individual differences. This study explores the influence of individual factors and social support on traumatic reactions in firefighters exposed to tragic events in the line of duty. A total of 164 Australian firefighters completed questionnaires targeting locus of control, self-efficacy, patterns of interpersonal relating, social support and level of emotional distress. Results indicate that individuals with feelings of insecurity, lack of personal control, and alienation from others were more likely to experience higher levels of depression and posttraumatic stress symptoms subsequent to exposure to traumatic events on the job.

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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.636
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.045
GPT teacher head0.342
Teacher spread0.297 · 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