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Record W2922484454 · doi:10.1186/s12889-019-6455-4

Levels and predictors of participation in integrated treatment programs for pregnant and parenting women with problematic substance use

2019· article· en· W2922484454 on OpenAlexafffundabout
Thao Le, Chris Kenaszchuk, Karen Milligan, Karen Urbanoski

Bibliographic record

VenueBMC Public Health · 2019
Typearticle
Languageen
FieldMedicine
TopicPrenatal Substance Exposure Effects
Canadian institutionsUniversity of VictoriaToronto Metropolitan UniversityCentre for Addiction and Mental Health
FundersCanadian Institutes of Health ResearchOntario Ministry of Health and Long-Term Care
KeywordsMedicineBiostatisticsPublic healthPromotion (chess)PsychiatryFamily medicineNursing

Abstract

fetched live from OpenAlex

BACKGROUND: Women who are seeking services for problematic substance use are often also balancing responsibilities of motherhood. Integrated treatment programs were developed to address the diverse needs of women, by offering a holistic and comprehensive mix of services that are trauma- and violence-informed, and focus on maternal and child health promotion and the development of healthy relationships. METHODS: Using system-level administrative data from a suite of outpatient integrated programs in Ontario, Canada, we described the clients and rates and predictors of treatment participation over a 7-year period (2008-2014; N = 5162). RESULTS: All participants were either pregnant or parenting children under 6 years old at admission to treatment. Retention (length of time between the first and last visit) averaged 124.9 days (SD = 185.6), with episodes consisting of 14.6 visits (SD = 28.6). The vast majority of women attended more than one visit (87.2%), typically returning within 2 weeks (mean 12.3 days, SD = 11.1). In addition to being pregnant or new mothers experiencing problematic substance use, most were unemployed, on social assistance, and single. CONCLUSIONS: Programs appeared to be able to successfully engage most women in treatment once they accessed the programs. Although rates of treatment participation did vary across subgroups defined by sociodemographic and admission characteristics, effect sizes tended to be small on average, providing little evidence in general of sociodemographic inequities in participation. Further work is needed to study the influence of program-level factors on participation, and how these link to maternal and child outcomes.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.390

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 head0.067
GPT teacher head0.312
Teacher spread0.245 · 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.

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

Citations29
Published2019
Admission routes3
Has abstractyes

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