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Record W4399906327 · doi:10.1111/acer.15394

Prevalence of fetal alcohol spectrum disorder in foster care: A scoping review

2024· review· en· W4399906327 on OpenAlexaff
Bailey Engesether, Mercedes Hoffner, Erika Johnson, Marilyn G. Klug, Svetlana Popova, Larry Burd

Bibliographic record

VenueAlcohol Clinical and Experimental Research · 2024
Typereview
Languageen
FieldMedicine
TopicPrenatal Substance Exposure Effects
Canadian institutionsPublic Health OntarioUniversity of TorontoSurrey Place CentreCentre for Addiction and Mental Health
Fundersnot available
KeywordsFetal Alcohol Spectrum DisorderFoster careMedicineAlcoholPsychologyPsychiatryClinical psychologyNursingPregnancyChemistryBiology

Abstract

fetched live from OpenAlex

The prevalence of fetal alcohol spectrum disorder (FASD) has been reported to be disproportionately high among children in foster care compared with the general population. However, updated prevalence estimates of infants and children with FASD in foster care or the prevalence of placement of children with FASD in foster care make this unclear. This study examines two questions. Firstly, what is the prevalence of FASD among infants and children in foster care? Secondly, what is the likelihood of placement in foster care for infants and children with FASD? This review was designed using PRISMA-SCR and JBI scoping review guidelines. Three databases were searched for the period June 2012 to June 2023: PubMed, Cumulative Index to Nursing and Allied Health Literature (CINAHL), and Google Scholar for all countries. Overall prevalence estimates were calculated using a complementary log-log link model along with 95% confidence intervals. Firstly, the estimated prevalence of FASD among infants and children in foster care was 18.8%. Secondly, among children diagnosed with FASD 30.5% are placed into foster care, reflecting greatly increased risk of placement of infants and children with FASD in foster care. We conclude that routine screening for FASD is needed to improve the identification of infants and children with FASD. Increased attention is also needed on developing strategies for FASD prevention. Recognition that nearly one of every three children with FASD will enter foster care demonstrates the need for increased funding, enhanced training and greater availability of services for families and children impacted by FASD.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.354
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.002
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 head0.248
GPT teacher head0.560
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.

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

Citations13
Published2024
Admission routes1
Has abstractyes

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