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Record W921068789 · doi:10.5206/eei.v25i2.7725

Assessment, Intervention, and Training Needs of Service Providers for Children with Intellectual Disabilities or Autism Spectrum Disorders and Concurrent Problem Behaviours

2015· article· en· W921068789 on OpenAlexafffundvenue
Mélina Rivard, Diane Morin, Carmen Dionne, Catherine Mello, Marc‐André Gagnon

Bibliographic record

VenueExceptionality Education International · 2015
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsUniversité du Québec à Trois-RivièresUniversité du Québec à Montréal
FundersMcGill University
KeywordsAutismService providerIntervention (counseling)PsychologyPsychological interventionIntellectual disabilityAutism spectrum disorderPerceptionPopulationNeeds assessmentService (business)Clinical psychologyMedical educationMedicinePsychiatry

Abstract

fetched live from OpenAlex

This study documented the perceived needs of therapists, specialists, and managers who work with children with intellectual disabilities (ID) and/or autism spectrum disorders (ASD) and concurrent problem behaviours (PBs). Seventy-five respondents from specialized PB and early childhood programs within eight public rehabilitation centres were surveyed. They were asked to describe current practices and perceived needs in terms of assessment, intervention, and training with respect to the target population. Overall, the perceptions of staff were consistent with the results of previous studies examining families’ perspectives. Salient themes include the need for specialized assessments for PBs in young children, collaboration between multiple service providers and families, and additional staff training in child development and interventions for PBs. These findings underscore the importance of offering diversified services adapted to the needs of children with PBs, their families, and their service providers.

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)0.003
metaresearch head score (Gemma)0.013
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
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 head0.080
GPT teacher head0.411
Teacher spread0.331 · 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

Citations10
Published2015
Admission routes3
Has abstractyes

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Same venueExceptionality Education InternationalSame topicFamily and Disability Support ResearchFrench-language works237,207