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Record W2159875157 · doi:10.3109/01942638.2014.978932

A Service Delivery Model for Children with DCD Based on Principles of Best Practice

2014· article· en· W2159875157 on OpenAlexaff
Chantal Camden, France Léger, Julie Morel, Cheryl Missiuna

Bibliographic record

VenuePhysical & Occupational Therapy In Pediatrics · 2014
Typearticle
Languageen
FieldPsychology
TopicChildren's Physical and Motor Development
Canadian institutionsMcMaster UniversityCentre de réadaptation Lethbridge-Layton-MackayUniversité de Sherbrooke
Fundersnot available
KeywordsPsychological interventionContext (archaeology)Service delivery frameworkService (business)PsychologyApplied psychologyFocus groupPerspective (graphical)Medical educationProcess managementSet (abstract data type)MedicineKnowledge managementNursingComputer scienceBusinessMarketing

Abstract

fetched live from OpenAlex

AIMS: In this perspective article, we propose the Apollo model as an example of an innovative interdisciplinary, community-based service delivery model for children with Developmental Coordination Disorder (DCD) characterized by the use of graduated levels of intensity and evidence-based interventions that focus on function and participation. METHODS: We describe the context that led to the creation of the Apollo model, describe the approach to service delivery and the services offered. RESULTS: The Apollo model has 5 components: first contact, service delivery coordination, community-, group-, and individual-interventions. This model guided the development of a streamlined set of services offered to children with DCD, including early-intake to share educational information with families, community interventions, inter-disciplinary and occupational therapy groups, and individual interventions. Following implementation of the Apollo model, wait-times decreased and the number of children receiving services increased, without compromising service quality. CONCLUSIONS: Lessons learned are shared to facilitate development of other practice models to support children with DCD.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.343
Threshold uncertainty score0.692

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.043
GPT teacher head0.331
Teacher spread0.287 · 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 teacher head, 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

Citations8
Published2014
Admission routes1
Has abstractyes

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