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Record W1978624246 · doi:10.1080/10926771.2013.845279

Addiction in Maternity: Prevalence of Mental Illness, Substance Use, and Trauma

2013· article· en· W1978624246 on OpenAlexaff
Isabelle A. Linden, Iris Torchalla, Michael Krausz

Bibliographic record

VenueJournal of Aggression Maltreatment & Trauma · 2013
Typearticle
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsUniversity of British ColumbiaSt. Paul's HospitalCentre for Advancing Health Outcomes
Fundersnot available
KeywordsMental illnessPsychiatryMedicineSubstance abuseSubstance useLife expectancyAddictionPovertyDual diagnosisExpectancy theoryClinical psychologyMental healthPsychologyPopulation

Abstract

fetched live from OpenAlex

Women living in vulnerable neighborhoods experience higher rates of poverty, homelessness, psychiatric issues, illicit substance use, rates of HIV, and a lowered life expectancy. The aim of the study was to further explore the history of mental illness and trauma in a sample of women (N = 31) who had recently given birth and had a substance use problem while pregnant. We investigated sociodemographic characteristics, history of trauma and post-traumatic stress disorder (PTSD), rates of substance use and dependence, and psychiatric symptoms. Childhood and adult traumatic experiences were found in the majority of the sample, and one-third presented with suspected PTSD diagnosis at the time of the interview. Women-centered services are in great demand, as well as trauma informed care, and further research on appropriate treatment for substance using, traumatized, women with a mental illness.

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)0.001
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 score0.010
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.024
GPT teacher head0.280
Teacher spread0.256 · 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

Citations19
Published2013
Admission routes1
Has abstractyes

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