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Record W4417296797 · doi:10.1093/pch/pxaf116.011

11 Provider perspectives on FASD diagnostic practices

2025· article· en· W4417296797 on OpenAlexaffabout
Alison Faber, Hilary Ho, Denise Somuah Asamoah, Sarah M. Hutchison, Katelynn Boerner, Tim F. Oberlander, Gurpreet Salh

Bibliographic record

VenuePaediatrics & Child Health · 2025
Typearticle
Languageen
FieldMedicine
TopicPrenatal Substance Exposure Effects
Canadian institutionsSunny Hill Health Centre for ChildrenUniversity of VictoriaUniversity of British Columbia
Fundersnot available
KeywordsThematic analysisFocus groupMultidisciplinary approachReflexivityBiopsychosocial modelFetal Alcohol Spectrum DisorderReferralData collection

Abstract

fetched live from OpenAlex

Abstract Background Fetal Alcohol Spectrum Disorder (FASD) is a diagnosis associated with complex, varied, and significant neurodevelopmental impairments. The clinical picture is frequently complicated by biopsychosocial and societal factors, as well as significant stigma. Furthermore, the referral and assessment process has historically been fraught with inequities, biases, and barriers to diagnosis, services, and supports. In Canada, FASD assessment often occurs through a time and resource intensive multidisciplinary assessment process. Objectives The purpose of our study is to better understand and document the experiences and unique challenges facing providers involved in FASD assessments, as well as collect proposed solutions to improve the process. Design/Methods Participants included clinicians involved in publicly funded FASD assessments in a Canadian provincial system, including developmental paediatricians, speech and language pathologists, psychologists, social workers, occupational therapists, nurse clinicians, case managers and general paediatricians. A total of 6 focus groups and 10 interviews (N=24) were conducted in April 2024 through July 2024. Seven participants also completed an anonymous follow-up survey which was included in the data analysis. The focus groups, interviews, and surveys explored clinicians’ experiences with the FASD diagnostic process, challenges they may face, approaches to cultural safety, and suggestions for improvement. Transcripts from the focus groups, interviews and surveys were analyzed using reflexive thematic analysis. This approach allows for engagement with the data while critically and transparently examining the perspectives and experiences that influence the knowledge generation process. Results Participants described the following: (1) finding the diagnostic label of FASD to be problematic, as many struggled with solely attributing a child’s developmental and behavioural challenges to prenatal alcohol exposure and worried about harm to birth mothers/families; (2) ethical dilemmas, such as confirming prenatal alcohol exposure and historical biases; (3) challenges and inconsistencies applying the Canadian diagnostic guidelines. Many clinicians expressed a desire to move towards a functional based approach to better describe and support complex children and youth with perinatal alcohol exposure. Conclusion Clinicians involved in FASD diagnostic assessments described feelings of frustration around the current diagnostic process and some hesitancy diagnosing children with FASD - pointing towards experiences of moral distress. There was considerable interest from participants to move toward a more function-based approach to diagnoses and recommendations for supports for children with prenatal alcohol exposure. Further studies are needed to examine the perspectives and lived experiences of youth and adults who have been diagnosed with 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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.046
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.131
Threshold uncertainty score0.260

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.046
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.003
Scholarly communication0.0040.002
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.000

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 head0.012
GPT teacher head0.314
Teacher spread0.301 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2025
Admission routes2
Has abstractyes

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