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Record W2327313360 · doi:10.2182/cjot.2011.79.5.6

Measurement properties of the MacHANd Performance Assessment: A pilot study

2012· article· en· W2327313360 on OpenAlexaffvenue
Tara Packham, Elizabeth C. M. Landman, Annemarie Muhic, Andrea Hebert, Pamela D. Ball

Bibliographic record

VenueCanadian Journal of Occupational Therapy · 2012
Typearticle
Languageen
FieldMedicine
TopicOrthopedic Surgery and Rehabilitation
Canadian institutionsMcMaster UniversitySouthlake Regional Health CenterHand and Upper Limb ClinicHotel Dieu Shaver Health and Rehabilitation CentreHamilton General Hospital
Fundersnot available
KeywordsReliability (semiconductor)Test (biology)Standardized testPhysical therapyPsychologyPsychometricsPhysical medicine and rehabilitationMedicineClinical psychology

Abstract

fetched live from OpenAlex

BACKGROUND: There is a need for a standardized, performance-based hand function assessment with strong psychometric properties to evaluate persons following a traumatic hand injury. PURPOSE: To conduct a preliminary investigation of the reliability and validity of the MacHANd performance assessment (MPA), a new standardized hand function test. METHODS: Forty-one people receiving treatment for hand injuries were evaluated using the MPA, Patient-rated Wrist and Hand Evaluation, and Jebsen-Taylor Hand Function Test. RESULTS: The MPA demonstrated adequate inter-rater reliability and excellent test-retest reliability, and it confirmed three validation hypotheses. IMPLICATIONS: This pilot study suggests that the MPA has good psychometric properties when used with individuals following a hand injury; however more research is needed.

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 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)0.024
metaresearch head score (Gemma)0.044
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.024
Threshold uncertainty score0.126

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.044
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.299
GPT teacher head0.354
Teacher spread0.054 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreMethods

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
Published2012
Admission routes2
Has abstractyes

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