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Record W2416992704 · doi:10.1080/10926771.2016.1152341

Understanding Social Factors in the Context of Trauma: Implications for Measurement and Intervention

2016· article· en· W2416992704 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

VenueJournal of Aggression Maltreatment & Trauma · 2016
Typearticle
Languageen
FieldPsychology
TopicPosttraumatic Stress Disorder Research
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsSocial supportIntervention (counseling)PsychologyAssociation (psychology)Construct (python library)Posttraumatic stressContext (archaeology)Clinical psychologySocial environmentDevelopmental psychologyPsychiatrySocial psychologyPsychotherapist

Abstract

fetched live from OpenAlex

One of the most important factors predicting the presence of posttraumatic stress disorder (PTSD) after trauma exposure is social support, yet the construct is theoretically complex and remains variably defined. To better inform the trauma literature on the impact of social factors, a theoretical review of social support and PTSD was conducted, and implications for measurement and intervention are outlined. Type of trauma, sex of participant, timing of social support, and support providers are described as significant moderators of the association between social factors and PTSD. The developmental trajectory of the association between social factors and PTSD occurrence is outlined, emphasizing the positive influence of social support initially following trauma, and the deterioration effect of PTSD symptoms on social support over the longer term. Possibilities for future research and intervention at multiple levels and at different time points are described.

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)0.001
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 score0.725
Threshold uncertainty score0.272

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.391
GPT teacher head0.437
Teacher spread0.045 · 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