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Physiotherapy interventions for head and trunk control in children with developmental disabilities: A scoping review protocol

2023· review· en· W4327710044 on OpenAlexaff
Shristi Shakya, Shradha S. Parsekar, Selvam Ramachandran, Shamantha Madapura S., Harikishan Balakrishna Shetty, Dana Anaby, Sivakumar Gopalakrishna, Vigneshwaran Venkatesan, Bhamini Krishna Rao

Bibliographic record

VenueF1000Research · 2023
Typereview
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsMcGill University
Fundersnot available
KeywordsCINAHLPsychological interventionRandomized controlled trialProtocol (science)MedicineCochrane LibraryGrey literatureTrunkMEDLINEPhysical medicine and rehabilitationPhysical therapyGerontologyAlternative medicineNursingPathologyBiology

Abstract

fetched live from OpenAlex

Background: Head and trunk control is prerequisite skill that maximizes engagement and participation in one’s environment by integrating vision, oromotor skill, arm control and respiration. Various physiotherapy and technology-based interventions have been utilized to facilitate head and trunk control in children with developmental disabilities. This scoping review is planned to map and summarize existing studies from the scientific literature on physiotherapy and technology-based interventions for head and trunk control in children with developmental disabilities. Methods: The scoping review will utilize the Joanna Briggs Institute scoping review methodology. The review will cover studies including children and adolescents aged between six months and 17 years 11 months 29 days, with developmental disabilities where in child finds difficulty in lifting its head and aligning head and trunk. We will include randomized controlled trial (RCT), non-RCT, quasi-experimental trial, and systematic reviews that have employed physiotherapy and technology-based interventions. Database-specific search strategy will be used to search records in Medline (PubMed and Web of Science), Embase, Scopus, CINAHL, PEDro, and Cochrane Library. Additionally, various grey literatures and clinical-trial registries will be searched. Two reviewers, independently, will screen and extract the data. Tables and visual representations will be utilized to present the extracted data. Registration details: The protocol has been registered in Open Science Framework, DOI: 10.17605/OSF.IO/B3RSU (22 nd August 2022)

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Protocol
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewlow
gptno category
Domain: not available · Genre: Protocol
About the Canadian research system: no · About a Canadian topic: no
Not applicablelow
models splitAgreement compares identical category sets and study designs across arms.

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)0.073
metaresearch head score (Gemma)0.056
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: Protocol · Consensus signal: Protocol
Teacher disagreement score0.103
Threshold uncertainty score0.384

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0730.056
Meta-epidemiology (narrow)0.0050.006
Meta-epidemiology (broad)0.0120.012
Bibliometrics0.0160.012
Science and technology studies0.0060.004
Scholarly communication0.0080.009
Open science0.0070.007
Research integrity0.0090.007
Insufficient payload (model declined to judge)0.1030.018

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 head0.166
GPT teacher head0.534
Teacher spread0.368 · 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

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designSystematic review · Not applicable
Domainnot available
GenreProtocol

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
Published2023
Admission routes1
Has abstractyes

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