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Record W2035504775 · doi:10.5014/ajot.2012.005553

Development and Validation of Tools for Evaluation of Orthosis Fabrication

2012· article· en· W2035504775 on OpenAlexaff
Andonia Stefanovich, Camille K. Williams, Pat McKee, Eric Hagemann, Heather Carnahan

Bibliographic record

VenueAmerican Journal of Occupational Therapy · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicDelphi Technique in Research
Canadian institutionsThe Wilson CentreWomen's College HospitalUniversity of Toronto
Fundersnot available
KeywordsChecklistDelphi methodCompetence (human resources)DelphiOccupational therapyReliability (semiconductor)Computer scienceRating scalePhysical therapyPsychologyMedicineArtificial intelligence

Abstract

fetched live from OpenAlex

This study is the first phase of research aimed at developing new educational approaches to enhance occupational therapy students' orthosis fabrication skills. Before the effectiveness of training can be determined, a method for evaluating performance must be established. Using the Delphi method, we developed a global rating scale and checklist for evaluating technical competence when fabricating metacarpophalangeal (MCP) joint-stabilizing orthoses. To determine the reliability and validity of these tools, three evaluators used them to assess and score orthotic fabrication performance by experienced and student occupational therapists. The results suggest that these measurement tools are valid and reliable indicators of the technical skills involved in fabricating an MCP joint-stabilizing orthosis. Future studies should focus on building on these tools to evaluate communication skills, technical skills for making other types of orthoses, and effectiveness of training 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)0.006
metaresearch head score (Gemma)0.001
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 score0.897
Threshold uncertainty score0.205

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
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 head0.405
GPT teacher head0.540
Teacher spread0.135 · 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
Published2012
Admission routes1
Has abstractyes

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