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Record W1974800001 · doi:10.1037/a0020139

Maternal mental health and integrated programs for mothers with substance abuse issues.

2010· article· en· W1974800001 on OpenAlexafffund
Alison Niccols, Karen Milligan, Wendy Sword, Lehana Thabane, Joanna Henderson, Ainsley Smith, Jennifer Liu, Susan M. Jack

Bibliographic record

VenuePsychology of Addictive Behaviors · 2010
Typearticle
Languageen
FieldMedicine
TopicMaternal Mental Health During Pregnancy and Postpartum
Canadian institutionsCentre for Addiction and Mental HealthMcMaster University
FundersCanadian Institutes of Health Research
KeywordsMental healthSubstance abusePsychologyMeta-analysisPsychiatryMedicine

Abstract

fetched live from OpenAlex

To examine the impact of integrated treatment programs (those with substance use treatment and pregnancy-, parenting-, or child-related services) on maternal mental health, we compiled a database of studies of integrated programs published between 1990 and 2007 with outcome data on maternal mental health. There were 18 cohort studies, 3 randomized trials, and 2 quasi-experimental studies. Of the five studies comparing integrated to nonintegrated programs, three studies provided enough information to allow for them to be combined in a meta-analysis. The average effect size was 0.23 (95% CI = 0.15 to 0.31, SE = 0.04), p < .001. There was no statistically significant heterogeneity among the studies, Q = 5.66, p = .059. This meta-analysis is the first systematic quantitative review of studies evaluating the impact of integrated programs on maternal mental health. Findings suggest that integrated programs may be associated with a small advantage over nonintegrated programs in improving maternal mental health. This review highlights the need for further research with improved methodology, study quality, and reporting to improve our understanding of how best to meet the mental health needs of mothers with substance abuse issues.

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)0.000
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 score0.015
Threshold uncertainty score0.505

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.021
GPT teacher head0.357
Teacher spread0.336 · 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

Citations44
Published2010
Admission routes2
Has abstractyes

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