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Record W4401621822 · doi:10.1177/08862605241270084

Health Problems Mediate the Effects of Adverse Childhood Experiences on the Frequency of Cannabis Use in a Sample of Pregnant and Breastfeeding Women

2024· article· en· W4401621822 on OpenAlexaboutno aff
Kathleen Kendall–Tackett, Stephen R. Poulin, Christine D. Garner

Bibliographic record

VenueJournal of Interpersonal Violence · 2024
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsnot available
Fundersnot available
KeywordsBreastfeedingCannabisMedicinePregnancyMediationPsychiatryPediatrics

Abstract

fetched live from OpenAlex

Many health organizations recommend that mothers avoid cannabis during pregnancy and breastfeeding because they are concerned about exposing infants to Δ-9-tetrahydrocannabinol (THC), the psychoactive substance in cannabis. Yet, data collected by the U.S. Centers for Disease Control demonstrate that a small percentage of mothers continue to use cannabis despite warnings. The frequency of cannabis use is an important variable because frequent use increases THC exposure. The present study examined two variables related to the frequency of cannabis use during pregnancy and breastfeeding: health problems and adverse childhood experiences (ACEs). We examined a possible mediation effect of health problems on the relationship between ACEs and the frequency of cannabis use during pregnancy and breastfeeding. Our sample was entirely comprised of 1,343 women who used cannabis during pregnancy and breastfeeding. We collected data online. The women were recruited from a Facebook group that supports pregnant and breastfeeding mothers who use cannabis. To be included, participants needed to be at least 18 years old and to have used cannabis while pregnant or breastfeeding. The sample was 79% White, 8% Hispanic, and 14% Black, and 1,199 currently resided in the United States, 76 in Canada, 11 in the United Kingdom, and the rest resided in 13 other countries. Ninety-three percent of the sample reported at least one ACE, and 59% reported 4 or more. Ninety-six percent reported that they were using cannabis to treat a health problem, and the number of health problems ranged from 0 to 8. Two mediation analyses found that the total number of ACEs increased the risk of health problems, which increased the frequency of cannabis use. ACE total was not significantly related to the frequency of use once health problems were accounted for. ACEs are related to the frequency of cannabis use in pregnant and breastfeeding women, but indirectly through trauma's impact on health problems. These findings suggest that practitioners might be able to lower the frequency of cannabis if they directly address health problems.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.241
Threshold uncertainty score0.575

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.020
GPT teacher head0.332
Teacher spread0.312 · 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 designQualitative
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

Citations4
Published2024
Admission routes1
Has abstractyes

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