Current practices, supports, and challenges in speech-language pathology service provision for autistic preschoolers
Bibliographic record
Abstract
Background: Speech-language pathology services are among the most frequently accessed services for young autistic children. Therefore, understanding the nature of these services, what challenges these clinicians face, and what supports they value is critical for developing appropriate policies and practices that can maximize positive outcomes for children and families. This study had two primary aims. The first was to examine the self-reported assessment and intervention practices of community-based Speech Language Pathologists (SLPs) and communicative disorders assistants (CDAs; who provide services under the supervision of a SLP) in supporting preschool children with suspected and diagnosed autism. The second aim was to identify barriers and supports (facilitators) to providing services in the community using the Consolidated Framework for Implementation Research (CFIR) as a framework. Methods: A cross-sectional online survey was used to collect qualitative and quantitative data from clinicians in Ontario Canada who were providing speech and language services to preschool children with suspected or diagnosed autism. Quantitative data were used to describe clinicians" practices, and qualitative data captured their perspectives on barriers and supports to providing services. Results: A total of 258 clinicians participated in the survey. On average, clinicians reported almost half of the preschoolers on their caseload had either diagnosed or suspected autism. There was consistency across the skill development areas assessed by SLPs, and targeted during therapy sessions, with the top four areas targeted being: foundational social communication, language, play and pragmatics. However, there was wide variation in speech and language assessment and intervention practices reported by this sample of clinicians (i.e., service delivery models, tools or programs used, length and duration of therapy services, level of collaboration with other professionals). Clinicians identified several barriers to providing services: limited funding and time, lack of inter-professional collaboration, difficulty accessing services, community messaging about autism services, family readiness and clinician knowledge. Supports (facilitators) included: access to autism-focused professional development, inter- and intra-professional collaboration, and access to additional supports in the community.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".