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The role of referral pathway to early intervention services for psychosis on 2-year inpatient and emergency service use

2024· article· en· W4392246553 on OpenAlexaff
Brannon Senger, Alissa Pencer, Candice E. Crocker, Patryk Simon, Bryanne Taylor, Philip G. Tibbo

Bibliographic record

VenueJournal of Psychiatric Research · 2024
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsNova Scotia Health AuthorityIzaak Walton Killam Health CentreDalhousie University
Fundersnot available
KeywordsReferralMedicineIntervention (counseling)Mental healthPsychosisPsychiatryHealth careFamily medicineMedical emergency

Abstract

fetched live from OpenAlex

This study examined the relationship between terminal referral source and subsequent urgent health service use in a Canadian early intervention service (EIS) for psychosis. Administrative health record data of emergency and inpatient mental health service use over a 2-year follow up from entry to EIS were retrospectively analyzed (n = 515). Negative binomial regression models were used to assess for the relationship between referral source and care outcomes. Compared to those referred from primary care services, the rate of urgent health care use was significantly greater for individuals referred to early intervention services from urgent care services while accounting for social and occupational functioning and psychotic symptom severity. Findings suggest that those referred from urgent services may be at an increased risk for subsequent urgent health care use while attending EIS for psychosis. Further research examining this relationship while incorporating additional relevant predictors is needed.

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)0.043
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 score0.125
Threshold uncertainty score0.249

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.043
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0030.003
Open science0.0030.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0130.001

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 head0.058
GPT teacher head0.404
Teacher spread0.347 · 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

Citations2
Published2024
Admission routes1
Has abstractno

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