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Record W3139378280 · doi:10.1177/1359105321999085

Childhood trauma, depression, resilience and suicide risk in individuals with inflammatory bowel disease

2021· article· en· W3139378280 on OpenAlexaff
Dean A. Tripp, Krista Jones, Valentina Mihajlovic, Sandra Westcott, Glenda MacQueen

Bibliographic record

VenueJournal of Health Psychology · 2021
Typearticle
Languageen
FieldHealth Professions
TopicAdolescent and Pediatric Healthcare
Canadian institutionsUniversity of CalgaryMcMaster UniversityQueen's University
Fundersnot available
KeywordsDepression (economics)MediationMedicinePsychological resilienceSuicide preventionPsychiatryClinical psychologyPoison controlInjury preventionIntervention (counseling)DiseasePsychologyInternal medicineMedical emergencyPsychotherapist

Abstract

fetched live from OpenAlex

Despite the prevalence of suicide risk in inflammatory bowel disease populations, research has yet to examine associations between childhood trauma, resilience, depression and suicide risk. In the present online study, 172 participants responded to measures of childhood trauma, resilience, depression and suicide risk. A moderated mediation revealed that resilience does not moderate the associations between childhood trauma, depressive symptoms and suicide risk. However, a serial mediation revealed that childhood trauma is associated with decreased resilience, which is related to higher depressive symptoms, and ultimately higher suicide risk, thus suggesting resilience and depression as significant intervention targets.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.037
GPT teacher head0.432
Teacher spread0.394 · 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 source (direct Gemma or distilled Codex), 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

Citations22
Published2021
Admission routes1
Has abstractyes

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