MétaCan
Menu
Back to cohort
Record W2527233231 · doi:10.1080/07380577.2016.1227893

Use of a Modified Canadian Occupational Performance Measure for Assistive Technology Outcomes in Postsecondary Education

2016· article· en· W2527233231 on OpenAlexaboutno aff
Ashley Pinkelman, Marla C. Roll, David Greene

Bibliographic record

VenueOccupational Therapy In Health Care · 2016
Typearticle
Languageen
FieldHealth Professions
TopicAssistive Technology in Communication and Mobility
Canadian institutionsnot available
Fundersnot available
KeywordsOccupational therapyAssistive technologyReliability (semiconductor)Measure (data warehouse)PsychologyReading (process)Test (biology)Medical educationApplied psychologyClinical psychologyComputer scienceMedicineHuman–computer interaction

Abstract

fetched live from OpenAlex

The Canadian Occupational Performance Measure (COPM) has been used to assess the effectiveness of assistive technology (AT). We explored whether a modified COPM was sensitive to change in perceived performance and satisfaction, and whether frequency of AT use resulted in greater change in the domains measured (reading, writing, note-taking, test-taking, and study skills). Significant interactions were found between time and use frequency with greater change in perceived performance in the daily-use group in several domains. In addition, the intra-class correlation showed moderate to strong equivalent forms reliability between two assessment formats. Based on these preliminary results, the ATRC-mCOPM was found to be a sensitive measure of perceived performance and satisfaction utilizing AT services in a postsecondary education setting.

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)0.004
metaresearch head score (Gemma)0.009
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 score0.701
Threshold uncertainty score0.602

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.003
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.142
GPT teacher head0.459
Teacher spread0.318 · 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

Citations3
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueOccupational Therapy In Health CareSame topicAssistive Technology in Communication and MobilityFrench-language works237,207