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A comparison of early psychosis treatment services using consensus and evidence‐based performance measures: moving towards setting standards

2009· article· en· W1993030063 on OpenAlexaffabout
Donald Addington, Ross Norman, Carol E. Adair, Rahul Manchanda, Emily McKenzie, Beth Mitchell, Cathy Pryce

Bibliographic record

VenueEarly Intervention in Psychiatry · 2009
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsWestern UniversityUniversity of Calgary
FundersHeritage Medical Research Institute
KeywordsdupPsychosisSchizophrenia (object-oriented programming)MedicineAntipsychoticEarly psychosisPsychiatryIntervention (counseling)Demography

Abstract

fetched live from OpenAlex

OBJECTIVE: This study used data from two Canadian early psychosis programs to assess the feasibility of using common performance measures and to assess the extent to which each program meets suggested standards for early intervention. METHODS: Data were extracted from administrative databases and supplemented by health records for 332 individuals admitted to two services in order to calculate values for 19 performance indicators for January 2000 to January 2004. Inter-rater reliability was established for data abstraction. RESULTS: The two samples had similar demographic and clinical profiles. There were no statistically significant differences in 1-, 2- and 3-year admission rates (year 1: 27% vs. 30%, P=0.625; year 2: 31% vs. 38%, P=0.248; year 3: 35% vs. 42%, P=0.260), duration of untreated psychosis (DUP) (24 vs. 28 weeks; P=0.844) and positive symptom remission at 1 year (72% vs. 78%; P=0.285). There were statistically significant differences between the two services in mean wait time (18 vs. 13 days; P=0.045), proportion of patients on second-generation anti-psychotics at 1 year (75% vs. 89%; P=0.002), and proportion of patients adherent to antipsychotic medication for a minimum of 12 months (76% vs. 83%; P=0.007). CONCLUSION: The data provides useful information on the feasibility of implementing key performance measures across early psychosis programs to assess the extent to which they are meeting standards for such 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.120
Threshold uncertainty score0.778

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.070
GPT teacher head0.412
Teacher spread0.342 · 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.

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

Citations14
Published2009
Admission routes2
Has abstractyes

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