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Record W2164382013 · doi:10.3109/17518423.2013.832431

Motor speech treatment protocol for developmental motor speech disorders

2013· article· en· W2164382013 on OpenAlexaff
Aravind Kumar Namasivayam, Margit Pukonen, Jennifer Hard, Rene Jahnke, Elaine Kearney, Robert M. Kroll, Pascal van Lieshout

Bibliographic record

VenueDevelopmental Neurorehabilitation · 2013
Typearticle
Languageen
FieldPsychology
TopicLanguage Development and Disorders
Canadian institutionsThe Speech and Stuttering InstituteToronto Rehabilitation InstituteUniversity of Toronto
FundersHealth Research BoardChildhood Apraxia of Speech Association of North America
KeywordsSpeech productionPsychologyAudiologyPsychosocialSensory systemMotor controlSpeech soundPopulationProtocol (science)Physical medicine and rehabilitationSpeech recognitionMedicineCognitive psychologyComputer scienceNeuroscience

Abstract

fetched live from OpenAlex

OBJECTIVE: This study examines the effect of the Motor Speech Treatment Protocol (MSTP), a multi-sensory hybrid treatment approach on five children (mean: 3;3 years; S.D. 0;1) with severe to profound speech sound disorders with motor speech difficulties. METHODS: A multiple probe design, replicated over five participants, was used to evaluate the effects of treatment on improving listeners' auditory and visual judgements of speech accuracy. RESULTS: All participants demonstrated significant change between baseline and maintenance conditions, with the exception of KM, who may have had underlying psychosocial, regulation and/or attention difficulties. The training- (practiced in treatment) and test-words (not practiced in treatment) both demonstrated positive change in all participants, indicating generalization of target features to untrained words. CONCLUSION: These results provide preliminary evidence that the MSTP, which integrates multi-sensory information and utilizes hierarchical goal selection, may positively impact speech sound production by improving speech motor control in this population.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0130.002

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 head0.023
GPT teacher head0.315
Teacher spread0.292 · 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 designNot applicable
Domainnot available
GenreMethods

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

Citations22
Published2013
Admission routes1
Has abstractyes

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