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Record W3142913461 · doi:10.1093/schizbullopen/sgab007

The First Episode Psychosis Services Fidelity Scale 1.0: Review and Update

2021· article· en· W3142913461 on OpenAlexaff
Donald Addington

Bibliographic record

VenueSchizophrenia Bulletin Open · 2021
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsInter-rater reliabilityFidelityScale (ratio)CLARITYRating scalePsychologyPsychosisClinical psychologyBrief Psychiatric Rating ScalePsychiatryApplied psychologyComputer scienceDevelopmental psychology

Abstract

fetched live from OpenAlex

Abstract The First Episode Psychosis Fidelity Scale, first published in 2016, is based on a list of essential components identified by systematic reviews and an international consensus process. The purpose of this paper was to present the FEPS-FS 1.0 version of the scale, review the results of studies that have examined the scale and provide an up-to-date review of evidence for each component and its rating. The First Episode Psychosis Services Fidelity Scale 1.0 has 35 components, which rate access and quality of health care delivered by early psychosis teams. Twenty-five components rate service components, and 15 components rate team functioning. Each component is rated on a 1–5 scale, and a rating of 4 is satisfactory. The service components describe services received by patients rather than staff activity. The fidelity rater completes ratings based on administrative data, health record review, and interviews. Fidelity raters from two multicenter studies provided feedback on the clarity and precision of component definitions and ratings. When administered by trained raters, the scale demonstrated good to excellent interrater reliability. The selection of components can be adjusted to rate programs serving patients with bipolar disorder or an attenuated psychosis syndrome. The scale can be used to assess and improve the quality of individual programs, compare programs and program networks. Researchers can use the scale as an outcome measure for implementation studies and as a process measure for outcome studies. Future research should focus on demonstrating predictive validity.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.586
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.015
GPT teacher head0.303
Teacher spread0.288 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreReview

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

Citations21
Published2021
Admission routes1
Has abstractyes

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