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Record W2527744760 · doi:10.1192/pb.bp.115.052290

The application of Rasch measurement theory to psychiatric clinical outcomes research

2016· article· en· W2527744760 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBJPsych Bulletin · 2016
Typearticle
Languageen
FieldDecision Sciences
TopicPsychometric Methodologies and Testing
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsRasch modelClassical test theoryItem response theoryOutcome (game theory)Polytomous Rasch modelTest (biology)Test theoryPsychologyPsychiatryPsychometricsComputer scienceMedicineClinical psychologyMathematicsDevelopmental psychology

Abstract

fetched live from OpenAlex

This commentary argues the importance of robust, meaningful assessment of clinical and functional outcomes in psychiatry. Outcome assessments should be fit for the purpose of measuring relevant concepts of interest in specific clinical settings. As well, the measurement model selected to develop and test assessments can be critical for guiding care. Three types of measurement models are presented: classical test theory, item response theory, and Rasch measurement theory. To optimise current diagnostic and treatment practices in psychiatry, careful consideration of these models is warranted..

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.

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)0.150
metaresearch head score (Gemma)0.300
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.863
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1500.300
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.002

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 head0.723
GPT teacher head0.610
Teacher spread0.113 · 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