MétaCan
Menu
Back to cohort
Record W2981043564 · doi:10.1111/add.14841

Fetal alcohol spectrum disorder: a systematic review of the cost of and savings from prevention in the United States and Canada

2019· review· en· W2981043564 on OpenAlexaffabout
Jacob R. Greenmyer, Svetlana Popova, Marilyn G. Klug, Larry Burd

Bibliographic record

VenueAddiction · 2019
Typereview
Languageen
FieldMedicine
TopicPrenatal Substance Exposure Effects
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental Health
Fundersnot available
KeywordsFetal Alcohol Spectrum DisorderMedicinePrimary preventionEnvironmental healthCost–benefit analysisPregnancyPolitical science

Abstract

fetched live from OpenAlex

BACKGROUND AND AIMS: Fetal alcohol spectrum disorder (FASD) is a preventable condition that imposes a significant financial burden on societies. Funding of FASD prevention is a small portion of the total expenditures associated with FASD. This paper aimed to review the literature on the costs of and savings from prevention of FASD and present a model for the United States and Canada of projected savings based on expansion of existing evidence-based prevention models. METHODS: A systematic review of published literature on the cost of FASD prevention was conducted and experts in the field were interviewed. Studies that reported the cost of primary prevention of FASD were eligible for further consideration. RESULTS: Applying evidenced-based prevention programs to women at highest risk to have a future child with FASD greatly reduces the cost of prevention. In the United States, one case of FASD can be prevented for as little as USD $20 200 - 47 615. Cost of prevention is considerably less expensive than cost of care for a case of FASD. CONCLUSION: Expansion of risk-based prevention strategies for fetal alcohol spectrum disorder in the United States and Canada would be an economically efficient and worthwhile investment for society.

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: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.022
Threshold uncertainty score0.876

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.016
GPT teacher head0.277
Teacher spread0.261 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations47
Published2019
Admission routes2
Has abstractyes

Explore more

Same venueAddictionSame topicPrenatal Substance Exposure EffectsFrench-language works237,207