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Record W3087367488 · doi:10.1097/pep.0000000000000730

A Survey of Pediatric Competencies in Entry-Level Physical Therapy Programs in Australia

2020· article· en· W3087367488 on OpenAlexaboutno aff
Emmah Baque, Taryn Jones, Andrea Bialocerkowski

Bibliographic record

VenuePediatric Physical Therapy · 2020
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsnot available
Fundersnot available
KeywordsCerebral palsyCurriculumPsychological interventionOccupational therapyMedicinePhysical therapyMedical prescriptionScale (ratio)Entry LevelPsychologyFamily medicineMedical educationNursing

Abstract

fetched live from OpenAlex

PURPOSE: To describe perspectives of pediatric physical therapy clinical facilitators on contemporary curricula for Australian entry-level physical therapy programs. METHODS: Physical therapy clinical facilitators completed an online survey based on the Academy of Pediatric Physical Therapy of the APTA essential competencies. RESULTS: Conditions including cerebral palsy, cystic fibrosis, and prematurity were highly rated by most participants to include in an entry-level program. Exercise prescription, goal-directed training, and group-based physical therapy were the highest rated interventions. Outcome measures considered important to include were the Alberta Infant Motor Scale and Goal Attainment Scale. Students should demonstrate knowledge and skills using relevant frameworks and have practical opportunities to interact with children. CONCLUSION: Pediatric clinical facilitators perceived that theoretical knowledge on frameworks, human development, movement skills, pediatric conditions, exercise prescription, and outcome measurement as well as face-to-face experiences with children are important to include in Australian entry-level physical therapy programs.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.454
GPT teacher head0.491
Teacher spread0.037 · 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.

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

Citations2
Published2020
Admission routes1
Has abstractyes

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