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Record W4392191100 · doi:10.3233/prm-230014

Clinical outcomes measurement in pediatric lower limb prosthetics: A scoping review

2024· review· en· W4392191100 on OpenAlexfundno aff
Kevin Koenig, Michelle J. Hall, Caroline Gormley, Mary K. Kaleta, Meghan E. Munger, Jennifer C. Laine, Sara J. Morgan

Bibliographic record

VenueJournal of Pediatric Rehabilitation Medicine · 2024
Typereview
Languageen
FieldEngineering
TopicProsthetics and Rehabilitation Robotics
Canadian institutionsnot available
FundersCanadian Institutes of Health Research
KeywordsCINAHLPhysical therapyQuality of life (healthcare)MedicinePhysical medicine and rehabilitationMEDLINEIntraclass correlationPsychometricsPatient-reported outcomeClinical psychologyPsychiatryPsychological interventionNursing

Abstract

fetched live from OpenAlex

OBJECTIVE: This study aimed to identify clinical measures that have been used to evaluate function, health related quality of life (HRQoL), and/or satisfaction in children who use lower limb prostheses (LLP). The data reported on psychometric properties for children who use LLP were collected for each measure. METHODS: First, PubMed, CINAHL, and Web of Science databases were searched using broad search terms to identify standardized outcome measures of function, HRQoL, and/or satisfaction with treatment used in pediatric LLP research published in 2001 or after. For each of the eligible measures found, a second search was performed to identify psychometric properties (e.g., validity, reliability) assessed with children who use LLP. RESULTS: Forty-four standardized outcome measures were identified from 41 pediatric LLP research articles. Five measures (i.e., Gait Outcomes Assessment for Lower Limb Differences, Functional Mobility Assessment, Child Amputee Prosthetics Project- Prosthesis Satisfaction Inventory, Child Amputee Prosthetics Project- Functional Scale Index, and Lower Limb Function Questionnaire) had data on psychometric properties for children who use LLP. CONCLUSIONS: Few studies report psychometric data for assessing the overall HRQoL, function, and/or satisfaction for children who use LLP. Further research is needed to validate or create new outcome measures that assess the HRQoL, satisfaction, and/or function of children who use LLP.

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)0.010
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.216
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.074
GPT teacher head0.397
Teacher spread0.323 · 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 designSystematic review
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

Citations2
Published2024
Admission routes1
Has abstractyes

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