MétaCan
Menu
Back to cohort
Record W2259813554 · doi:10.1176/appi.ps.201500085

Use of Mental Health Services by Youths and Young Adults Before and During Correctional Custody: A Population-Based Study

2016· article· en· W2259813554 on OpenAlexafffundabout
Saba Khan, Maria Chiu, Alexander I. F. Simpson, Astrid Guttmann, Nathaniel Jembere, Paul Kurdyak

Bibliographic record

VenuePsychiatric Services · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsInstitute for Clinical Evaluative Sciences
FundersCanadian Institutes of Health Research
KeywordsMental healthPsychiatrySchizophrenia (object-oriented programming)PopulationMedicineYoung adultPsychologyGerontologyEnvironmental health

Abstract

fetched live from OpenAlex

OBJECTIVE: The authors measured use of mental health services among young people before and during incarceration. METHODS: Administrative data were used to describe mental health services received by 13,919 youths and young adults (ages 12-24) while incarcerated in Ontario, Canada, correctional centers (physician visits, April 1, 2010-March 31, 2012) and, for a subset of the population, during the five years prior to incarceration. RESULTS: Forty-two percent had a mental health-related visit during incarceration. Thirty-five percent had no mental health contact for five years before the beginning of the correctional episode. Forty percent of individuals with schizophrenia had a psychiatric hospitalization in the year before entering custody. CONCLUSIONS: For one-third of young people with a mental health visit while incarcerated, the visit was the first mental health contact in at least five years. Yet high use of psychiatric services before entering custody among individuals with schizophrenia may indicate gaps in continuity of mental health care.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.196
Threshold uncertainty score0.390

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.008
GPT teacher head0.276
Teacher spread0.268 · 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

Citations6
Published2016
Admission routes3
Has abstractyes

Explore more

Same venuePsychiatric ServicesSame topicCriminal Justice and Corrections AnalysisFrench-language works237,207