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Record W2997999294 · doi:10.5014/ajot.2020.032052

Evaluating the Measurement Properties of the ScanCourse, a Dual-Task Assessment of Visual Scanning

2019· article· en· W2997999294 on OpenAlexaff
Paige Lund, Caitlyn Moir, Lisa Kristalovich, W. Ben Mortenson

Bibliographic record

VenueAmerican Journal of Occupational Therapy · 2019
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsVancouver Coastal Health Research InstituteUniversity of British ColumbiaInternational Collaboration On Repair DiscoveriesVancouver Coastal HealthPeace Arch Hospital
Fundersnot available
KeywordsIntraclass correlationInter-rater reliabilityReliability (semiconductor)PsychologyConstruct validityConfidence intervalStandard errorTest (biology)Physical medicine and rehabilitationPhysical therapyAudiologyStatisticsMedicinePsychometricsRating scaleDevelopmental psychologyMathematics

Abstract

fetched live from OpenAlex

IMPORTANCE: The ScanCourse is used by occupational therapists to evaluate visual scanning ability during locomotion. Its measurement properties have not been examined. OBJECTIVE: To assess the interrater reliability, test-retest reliability, and construct validity of the ScanCourse. DESIGN: This study involved data collection at two time points. To assess test-retest reliability, the ScanCourse was administered twice within a 2-week period. To assess interrater reliability, a second rater was present for one session. To assess level of agreement, a Bland-Altman plot was created. To assess absolute reliability, the standard error of measurement was calculated. To evaluate construct validity, the results of the ScanCourse were compared with results of the Bells Test and Trail Making Test A and B. SETTING: Rehabilitation hospital. PARTICIPANTS: Forty-one patients with neurological impairments. Outcomes and Measures: The ScanCourse (participants identify numbered cards placed on both sides of a hallway at various heights during locomotion). RESULTS: The ScanCourse was found to have excellent interrater reliability (intraclass correlation coefficient [ICC] [1,1] = .998; 95% confidence interval [CI] [.996-.999]), test-retest reliability (ICC [1,1] = .912; 95% CI [.811-.959]), a high level of agreement, and a low standard error of measurement (.503), and it was found to be significantly correlated with Trails A (rs = -.436, p = .009) and B (rs = -.364, p = .029). CONCLUSIONS AND RELEVANCE: The assessment was found to have strong measurement properties, and it is therefore an appropriate tool for assessing dual-task visual scanning among those with neurological impairments. What This Article Adds: This research demonstrates that the ScanCourse is reliable between raters and over time and that scores on the measure vary as anticipated with scores on a related measure, which provides evidence of its validity. These findings support its use in practice.

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)0.011
metaresearch head score (Gemma)0.047
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 score0.011
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.047
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.145
GPT teacher head0.431
Teacher spread0.287 · 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".

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Citations2
Published2019
Admission routes1
Has abstractyes

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