Parents’ perspectives on speech-language assessment for their preschool-aged children: A scoping review
Bibliographic record
Abstract
PURPOSE: Assessment allows speech-language pathologists to identify clients' strengths and needs while laying the foundation for the therapeutic relationship. However, the extent to which parents' experiences with assessment has been explored in the literature is unclear. The purposes of this review were to: a) Identify and summarise the available literature on parents' experiences with speech-language assessment for their preschool-aged children, and b) identify gaps in the literature. METHOD: Using an established framework for scoping reviews, the authors conducted a search of seven databases including literature up to April 2024. Two researchers independently reviewed articles for inclusion and discussed discrepancies, and a third researcher provided input when consensus could not be reached. Data extracted included study aims, participant information, and the aspects of the assessment process including the lead-up to the assessment, the assessment itself, receiving a diagnosis, and interim supports following the assessment. RESULT: Ten studies met inclusion criteria, however, only three studies were focussed on parents' experiences with speech-language assessment. CONCLUSION: In the included studies, aspects of assessment have been addressed but with limited depth and breadth. To date, the perspectives studied have primarily been those of monolingual, English-speaking mothers. Proposed reporting considerations are discussed, and clinical and research implications are explored.
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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 | 0.011 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".