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Record W4389391198 · doi:10.1186/s13690-023-01221-0

The role of general practitioners in Reunion in detecting alcohol use in pregnant women and identifying fetal alcohol spectrum disorder: a qualitative study

2023· article· en· W4389391198 on OpenAlexaff
Sébastien Leruste, Louise Delfarguiel, Bérénice Doray, Coralie Loubaresse, Laëtitia Sennsfelder, Thierry Maillard, Catherine Marimoutou, Michel Spodenkiewicz

Bibliographic record

VenueArchives of Public Health · 2023
Typearticle
Languageen
FieldMedicine
TopicPrenatal Substance Exposure Effects
Canadian institutionsMcGill UniversityDouglas Mental Health University Institute
Fundersnot available
KeywordsMedicineQualitative researchGrounded theoryFetal alcohol syndromePsychiatryFetal Alcohol Spectrum DisorderFamily medicineFocus groupClinical psychologyNursingPregnancyDevelopmental psychologyPsychology

Abstract

fetched live from OpenAlex

BACKGROUND: Fetal Alcohol Spectrum Disorder (FASD) is the leading cause of non-genetic intellectual disability and social maladjustment in children. International guidelines recommend abstinence from alcohol during pregnancy. Réunion is the most affected of all French regions with an estimated Fetal Alcohol Spectrum (FAS) prevalence of 1.2‰ births. General practitioners (GPs) are at the forefront of identifying patients with FASD. OBJECTIVE: To understand how GPs identify FASD. METHODS: Qualitative study using a grounded theory approach, through semi-structured face-to-face interviews with GPs. Interviews were conducted with the aim of reaching theoretical saturation. These were transcribed verbatim and then analyzed by four researchers to ensure triangulation of the data. RESULTS: GPs reported barriers to the identification of FASD: challenges in overcoming social taboos and paradoxical injunctions, the influence of limited knowledge and experience, non-specific and highly variable symptoms, ambiguous classification and method of diagnosis involving the mobilization of a multidisciplinary team and lengthy consultations. Conversely, they felt competent to identify neurodevelopmental disorders of any cause, but were concerned about the long waiting time to access specialized care. From the perspective of GPs, it is crucial to prioritize promotion and training aimed at improving the identification and coordination of care pathways for children diagnosed with neurodevelopmental disorders, such as 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)0.004
metaresearch head score (Gemma)0.002
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 score0.289
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.057
GPT teacher head0.371
Teacher spread0.313 · 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

Citations2
Published2023
Admission routes1
Has abstractyes

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