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Record W1540806214

Resourcefulness as a Factor in Recovery From Accident Related Trauma Among Polish Immigrants in Canada

2014· article· en· W1540806214 on OpenAlexaboutno aff
A.B. Wolanczyk

Bibliographic record

VenueEuropean Health Psychologist · 2014
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsnot available
Fundersnot available
KeywordsBeck Depression InventoryBeck Anxiety InventoryDepression (economics)PsychopathologyAnxietyPsychologyClinical psychologyMajor depressive disorderPsychiatry
DOInot available

Abstract

fetched live from OpenAlex

Background Psychopathological reactions are common occurrences after accident related trauma. This study intended to find out whether psychological resources can be seen as a factor preventing a Major Depressive Disorder after trauma. Methods 89 immigrants were examined. The average age was 46.6 years. 61% of the group were married. MVA were 80% and work-related 20%. The level of psychological resources of those with MDD diagnosis was compared to those diagnosed with PTSD, anxiety, adjustment and pain disorders. The measure of resources was the 18 scales of the Resourcefulness for Recovery Inventory. The severity of depression was measured by the Beck Depression Inventory II. Findings On every measure of resources those who responded to the accident with MDD had lower scores that those who did not (p = .0001). Among the most important resources seem to be: Hope and Expectations, Self-Responsibility, Positive Emotions. A further finding is that in the group of RRI scales called Health Promoting Factors those with MDD were especially low on the scale referring to Acceptance of Reality. The severity of depression measured by Beck Depression Inventory II was significantly correlated (r = 0,5) with a low level of Fundamental Values. Conclusion Our findings indicate that an adaptive reaction to MVA or work related accidents is associated with a high level of internal resources which are also needed for recovery from post traumatic conditions.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.101
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.029
GPT teacher head0.315
Teacher spread0.286 · 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.

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
Published2014
Admission routes1
Has abstractyes

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