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Record W4282945650 · doi:10.1097/pep.0000000000000915

Pediatric Assessments for Preschool Children in Digital Physical Therapy Practice: Results From a Scoping Review

2022· review· en· W4282945650 on OpenAlexaff
Nathalie Trottier, Karen Hurtubise, Cherie Zischke, Chantal Camden

Bibliographic record

VenuePediatric Physical Therapy · 2022
Typereview
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsObservational studyContext (archaeology)Scope (computer science)Descriptive statisticsCardiorespiratory fitnessThematic analysisPsychologyMedicinePhysical therapyComputer scienceQualitative research

Abstract

fetched live from OpenAlex

PURPOSE: To examine and map the extent and scope of pediatric physical therapy assessments previously used in the digital context. METHODS: A 6-step evidence-based scoping methodological framework was used. Articles containing assessments conducted by a physical therapist using technology to assess a child aged 0 to 5 years were included and synthesized using descriptive statistics and thematic analysis. RESULTS: Eighteen studies identifying 25 assessments were eligible. Asynchronous observational developmental instruments administered in the child's natural environment to those at risk or presenting with neurodevelopmental conditions were the most common. There is a need for detailed procedures and training for caregivers and clinicians. CONCLUSION: Limited research exists on the use of pediatric physical therapy assessments for young children with musculoskeletal and cardiorespiratory conditions in a digital context. The development of new instruments or modifications of existing ones should be considered and be accompanied by detailed administration protocols and user guides.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.969
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.068
GPT teacher head0.421
Teacher spread0.353 · 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 designOther design
Domainnot available
GenreReview

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

Citations5
Published2022
Admission routes1
Has abstractyes

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