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Mental Health Service Use Before First Diagnosis of a Psychotic Disorder

2024· article· en· W4399774813 on OpenAlexaffabout
Wanda Tempelaar, Nicole Kozloff, Emilie Mallia, Aristotle N. Voineskos, Paul Kurdyak

Bibliographic record

VenueJAMA Psychiatry · 2024
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsUniversity of TorontoInstitute for Clinical Evaluative SciencesCentre for Addiction and Mental Health
Fundersnot available
KeywordsPsychiatryMental healthPsychologySchizophrenia (object-oriented programming)MEDLINEMental health serviceMedicinePolitical science

Abstract

fetched live from OpenAlex

Importance: Characterizing mental health service use trajectories preceding diagnosis of a psychotic disorder may help identify individuals at highest risk and in which settings they are at highest risk. Objective: To examine mental health service use and diagnostic trajectories before first diagnosis of psychotic disorder and identify utilization and diagnostic patterns. Design, Setting, and Participants: This population-based, retrospective cohort study used linked provincial health administrative data. The sample included individuals aged 15 to 29 years diagnosed with a psychotic disorder in Ontario, Canada, between April 1, 2012, and March 31, 2018. These individuals were matched to individuals with a diagnosis of a mood disorder. Data were analyzed from November 2018 to November 2019. Main Outcomes and Measures: The main outcomes were rates, timing, and setting of mental health-related service use and associated diagnoses in the 3 years before the index disorder among individuals first diagnosed with a psychotic disorder compared with those first diagnosed with a mood disorder. Results: A total of 10 501 individuals with a first diagnosis of psychotic disorder were identified (mean [SD] age, 21.55 [3.83] years; 72.1% male). A total of 72.2% of individuals had at least 1 mental health service visit during the 3 years before their first psychotic disorder diagnosis, which was significantly more than matched controls with a first mood disorder diagnosis (66.8%) (odds ratio [OR], 1.34; 95% CI, 1.26-1.42). Compared with individuals diagnosed with a mood disorder, individuals diagnosed with a psychotic disorder were significantly more likely to have had mental health-related hospital admissions (OR, 3.98; 95% CI, 3.43-4.62) and emergency department visits (OR, 2.27; 95% CI, 2.12-2.43) in the preceding 3 years. Those with psychotic disorders were more likely to have had prior diagnoses of substance use disorders (OR, 2.57; 95% CI, 2.35-2.81), other disorders (personality disorders, developmental disorders) (OR, 1.75; 95% CI, 1.61-1.90), and self-harm (OR, 1.64; 95% CI, 1.36-1.98) in the past 3 years compared with those diagnosed with mood disorders. Conclusions and Relevance: This study found that in the 3 years prior to an index diagnosis, individuals with a first diagnosis of psychotic disorder had higher rates of mental health service use, particularly emergency department visits and hospitalizations, compared with individuals with a first diagnosis of a mood disorder. Individuals with psychotic disorders also had a greater number of premorbid diagnoses. Differences in health service utilization patterns between those with a first psychotic disorder diagnosis vs a first mood disorder diagnosis suggest distinct premorbid trajectories that could be useful for next steps in prediction and prevention research.

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)0.000
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 score0.283
Threshold uncertainty score0.834

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.018
GPT teacher head0.317
Teacher spread0.299 · 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

Citations6
Published2024
Admission routes2
Has abstractyes

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