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Record W1969686689 · doi:10.1186/1471-2431-12-69

Health professionals’ perceptions about the adoption of existing guidelines for the diagnosis of fetal alcohol spectrum disorders in Australia

2012· article· en· W1969686689 on OpenAlexaboutno aff
Rochelle Watkins, Elizabeth Elliott, Raewyn Mutch, Jane Latimer, Amanda Wilkins, Janet M Payne, Heather Jones, Sue Miers, Elizabeth Peadon, Anne McKenzie, Elizabeth Russell, James Fitzpatrick, Colleen O’Leary, Jane Halliday, Lorian Hayes, Lucy Burns, Maureen Carter, Carol Bower

Bibliographic record

VenueBMC Pediatrics · 2012
Typearticle
Languageen
FieldMedicine
TopicPrenatal Substance Exposure Effects
Canadian institutionsnot available
FundersNational Health and Medical Research CouncilMedical Research CouncilAustralian Government
KeywordsMedicineGuidelineFamily medicineMEDLINEHealth professionalsPerceptionHealth carePathologyPsychology

Abstract

fetched live from OpenAlex

BACKGROUND: Despite the availability of five guidelines for the diagnosis of fetal alcohol spectrum disorders (FASD), there is no national endorsement for their use in diagnosis in Australia. In this study we aimed to describe health professionals' perceptions about the adoption of existing guidelines for the diagnosis of FASD in Australia and identify implications for the development of national guidelines. METHODS: We surveyed 130 Australian and 9 international health professionals with expertise or involvement in the screening or diagnosis of FASD. An online questionnaire was used to evaluate participants' familiarity with and use of five existing diagnostic guidelines for FASD, and to assess their perceptions about the adoption of these guidelines in Australia. RESULTS: Of the 139 participants surveyed, 84 Australian and 8 international health professionals (66.2%) responded to the questions on existing diagnostic guidelines. Participants most frequently reported using the University of Washington 4-Digit Diagnostic Code (27.2%) and the Canadian guidelines (18.5%) for diagnosis. These two guidelines were also most frequently recommended for adoption in Australia: 32.5% of the 40 participants who were familiar with the University of Washington 4-Digit Diagnostic Code recommended adoption of this guideline in Australia, and 30.8% of the 26 participants who were familiar with the Canadian guidelines recommended adoption of this guideline in Australia. However, for the majority of guidelines examined, most participants were unsure whether they should be adopted in Australia. The adoption of existing guidelines in Australia was perceived to be limited by: their lack of evidence base, including the appropriateness of established reference standards for the Australian population; their complexity; the need for training and support to use the guidelines; and the lack of an interdisciplinary and interagency model to support service delivery in Australia. CONCLUSIONS: Participants indicated some support for the adoption of the University of Washington or Canadian guidelines for FASD diagnosis; however, concerns were raised about the adoption of these diagnostic guidelines in their current form. Australian diagnostic guidelines will require evaluation to establish their validity in the Australian context, and a comprehensive implementation model is needed to facilitate improved diagnostic capacity in Australia.

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)0.036
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 score0.043
Threshold uncertainty score0.086

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.036
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.158
GPT teacher head0.426
Teacher spread0.268 · 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

Citations109
Published2012
Admission routes1
Has abstractyes

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