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Record W2065010475 · doi:10.2174/1874325001509010057

Test-Retest Reliability and Convergent Validity of a Computer Based Hand Function Test Protocol in People with Arthritis

2015· article· en· W2065010475 on OpenAlexafffund
Cynthia Srikesavan, Barbara Shay, Tony Szturm

Bibliographic record

VenueThe Open Orthopaedics Journal · 2015
Typearticle
Languageen
FieldNeuroscience
TopicMotor Control and Adaptation
Canadian institutionsUniversity of Manitoba
FundersCanadian Arthritis Network
KeywordsIntraclass correlationMedicineGrip strengthConvergent validityPhysical medicine and rehabilitationPhysical therapyReliability (semiconductor)Test (biology)DashHand strengthTask (project management)WristConstruct validityProtocol (science)Criterion validityConcurrent validityComputer sciencePsychometricsSurgeryClinical psychology

Abstract

fetched live from OpenAlex

OBJECTIVES: A computer based hand function assessment tool has been developed to provide a standardized method for quantifying task performance during manipulations of common objects/tools/utensils with diverse physical properties and grip/grasp requirements for handling. The study objectives were to determine test-retest reliability and convergent validity of the test protocol in people with arthritis. METHODS: Three different object manipulation tasks were evaluated twice in forty people with rheumatoid arthritis (RA) or hand osteoarthritis (HOA). Each object was instrumented with a motion sensor and moved in concert with a computer generated visual target. Self-reported joint pain and stiffness levels were recorded before and after each task. Task performance was determined by comparing the object movement with the computer target motion. This was correlated with grip strength, nine hole peg test, Disabilities of Arm, Shoulder, and Hand (DASH) questionnaire, and the Health Assessment Questionnaire (HAQ) scores. RESULTS: The test protocol indicated moderate to high test-retest reliability of performance measures for three manipulation tasks, intraclass correlation coefficients (ICCs) ranging between 0.5 to 0.84, p<0.05. Strength of association between task performance measures with self- reported activity/participation composite scores was low to moderate (Spearman rho <0.7). Low correlations (Spearman rho < 0.4) were observed between task performance measures and grip strength; and between three objects' performance measures. Significant reduction in pain and joint stiffness (p<0.05) was observed after performing each task. CONCLUSION: The study presents initial evidence on the test retest reliability and convergent validity of a computer based hand function assessment protocol in people with rheumatoid arthritis or hand osteoarthritis. The novel tool objectively measures overall task performance during a variety of object manipulation tasks done by tracking a computer based visual target. This allows an innovative method of assessing performance than considering the time taken to complete a task or relying on subjective measures of self-reports on a limited range of objects and tasks covered. In addition, joint pain and stiffness levels before and after a manipulation task are tracked, which is lacking in other hand outcome measures. Performance measures during a broad range of object manipulation tasks relate to many activities relevant to life role participation. Therefore, task performance evaluation of common objects, utensils, or tools would be more valuable to gauge the difficulties encountered in daily life by people with arthritis. Future studies should consider a few revisions of the present protocol and evaluate a number of different objects targeting strength, fine, and gross dexterity based tasks for a broader application of the tool in arthritis populations.

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)0.016
metaresearch head score (Gemma)0.041
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.083

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.041
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.050
GPT teacher head0.277
Teacher spread0.227 · 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
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

Citations5
Published2015
Admission routes2
Has abstractyes

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