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Record W2764252047 · doi:10.1093/pch/20.5.e95a

170: Community General Paediatricians' Barriers to Providing Autism Spectrum Disorder Diagnoses

2015· article· en· W2764252047 on OpenAlexaff
Melanie Penner, Gillian King, Evdokia Anagnostou, Michelle Shouldice, Charlotte Moore Hepburn

Bibliographic record

VenuePaediatrics & Child Health · 2015
Typearticle
Languageen
FieldHealth Professions
TopicChild and Adolescent Health
Canadian institutionsHolland Bloorview Kids Rehabilitation Hospital
Fundersnot available
KeywordsMedical diagnosisAutism spectrum disorderThematic analysisPsychological interventionQualitative researchMedicineAutismClinical psychologyFamily medicinePsychologyPsychiatryPediatricsPathology

Abstract

fetched live from OpenAlex

Wait times for diagnosis of autism spectrum disorders (ASD) may negatively impact outcomes by delaying access to early interventions. Community general pediatricians (CGPs) are often consulted in cases of suspected ASD, and may play a role in increasing ASD diagnostic capacity in the community setting. The objective of this study was to explore the perspectives of CGPs regarding their role in the system of ASD diagnoses using qualitative methods. We performed a phenomenological qualitative study of CGPs' experiences with cases of suspected ASD. Two groups of CGPs were sampled to provide varying perspectives: CGPs that had referred patients with suspected ASD for a subspecialist assessment, and CGPs that regularly attended ASD educational events. Individual in-depth interviews were recorded and transcribed. Two investigators coded each interview. Thematic saturation was reached when two successive interviews did not generate new codes. Texts were analyzed using a grounded theory approach. A preliminary theoretical framework was developed, summarized and sent to participants with a request for feedback. This feedback was incorporated into the final theoretical framework. Eleven in-depth interviews were conducted (six males, five females; mean years in practice 17.1). Participants described three elements to the process of assessment: diagnostic determination, communication of the diagnosis, and management of the diagnosis. Each element contains potential barriers to assigning a diagnosis of ASD. Diagnostic determination is affected by patient factors (such as age, severity, and comorbidities), family factors (the reliability of the historian), and physician factors (such as training, access to informal expert consultation, and interest in ASD). When communicating the diagnosis, it is important that families know enough, but not too much, about ASD; families who know too much are perceived to need an “expert” opinion. Participants described a significant emotional burden and were very sensitive to the impact of the diagnosis. They feel ill equipped to deal with the fragmented service delivery system for ASD. Helping families to access services is time-consuming, poorly remunerated, and less satisfying than other areas of pediatric practice. Though CGPs are frequently consulted on cases of suspected ASD, they experience many barriers to making a diagnosis, leading to increased subspecialist referrals. Efforts to improve diagnostic capacity in this group must focus not only on diagnostic determination, but also on communicating the diagnosis and efficiently connecting families to resources.

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)0.009
metaresearch head score (Gemma)0.044
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.044
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.003
Scholarly communication0.0030.003
Open science0.0020.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.041
GPT teacher head0.360
Teacher spread0.319 · 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 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

Citations1
Published2015
Admission routes1
Has abstractyes

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