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Record W2142090099 · doi:10.5014/ajot.56.1.60

Development of a Standardized Instrument To Assess Computer Task Performance

2002· article· en· W2142090099 on OpenAlexaff
Claire Dumont, Claude Vincent, Barbara Mazer

Bibliographic record

VenueAmerican Journal of Occupational Therapy · 2002
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsJewish Rehabilitation HospitalUniversité Laval
Fundersnot available
KeywordsCronbach's alphaConstruct validityIntraclass correlationReliability (semiconductor)Test (biology)Internal consistencyPsychologyTask (project management)Construct (python library)PsychometricsApplied psychologyClinical psychologyComputer scienceEngineering

Abstract

fetched live from OpenAlex

OBJECTIVE: The purpose of this study was to determine the psychometric properties of the Assessment of Computer Task Performance, specifically, the test-retest reliability, internal consistency, construct validity, and ability to discriminate between known groups. METHOD: This assessment comprises 14 standardized and timed tasks. It was administered to 24 persons with upper-extremity impairments and 30 with no impairments by a trained occupational therapist. To assess the test-retest reliability, participants in the impaired group were retested within 2 to 7 days. Intraclass correlation coefficients were calculated to determine test-retest reliability. Internal consistency was assessed with Cronbach's alpha, and factor analysis was conducted to examine construct validity. The Mann Whitney U Test was used to assess the test's ability to discriminate between the groups. RESULTS: Results indicated that the tool has excellent reliability and internal consistency, can discriminate between groups, and has appropriate construct validity. CONCLUSION: The Assessment of Computer Task Performance provides occupational therapists with an accurate test to measure computer performance and can assist them in providing computer access services.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.851
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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)0.0010.000

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 head0.297
GPT teacher head0.492
Teacher spread0.195 · 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 designOther design
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

Citations39
Published2002
Admission routes1
Has abstractyes

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