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Record W4386534927 · doi:10.1016/j.ijlp.2023.101921

Forensic psychiatry patients, services, and legislation in Nunavut and Greenland

2023· article· en· W4386534927 on OpenAlexaffabout
Casey Upfold, Christian Jentz, Parnûna Heilmann, Naaja Nathanielsen, Gary Chaimowitz, Lisbeth Uhrskov Sørensen

Bibliographic record

VenueInternational Journal of Law and Psychiatry · 2023
Typearticle
Languageen
FieldPsychology
TopicMental Health Treatment and Access
Canadian institutionsMcMaster UniversitySt. Joseph’s Healthcare Hamilton
FundersRegion MidtjyllandAarhus UniversitetshospitalAarhus Universitet
KeywordsPsychiatryForensic psychiatryMental healthLegislationMedicinePopulationHealth careEnvironmental healthPolitical scienceLaw

Abstract

fetched live from OpenAlex

Circumpolar regions face unique challenges in establishing and maintaining mental health care systems, including forensic psychiatry services. The scarcity of data and lack of evidence concerning the forensic psychiatry patient (FPP) populations of Nunavut and Greenland exacerbates the challenges of informing best practices and healthcare planning. By comparing the prevalence of forensic psychiatry patients, the mental health care services, and the legislation in these two relatively similar but unique regions, insight may be gained that can help inform healthcare planning. This cross-sectional study includes all forensic psychiatry in- and outpatients in one year from Nunavut (2018) and on February 29, 2020, in Greenland. The Greenland sample (n = 93) was nearly four times larger than the Nunavut sample (n = 15) at the population level. Despite considerable differences in forensic legislation and service supply, the forensic psychiatry patients in the two areas share several similarities. A total of 87% (n = 13) in the Nunavut sample were diagnosed with a DSM-5 schizophrenia spectrum disorder or other psychotic disorder. In Greenland, 82% (n = 76) were diagnosed with an ICD-10 F2 diagnosis (schizophrenia, schizotypal and delusional disorders). Approximately 2/3 of the patients in both populations were diagnosed with substance use disorder, and 60% of the Nunavut FPP received long-acting antipsychotic injections versus 62% in Greenland. Nearly half of the FPPs in both populations had never been convicted prior to entering the forensic psychiatry system; Nunavut 45% versus Greenland 47%. A substantial proportion of Greenlandic FPPs were outpatients compared to Nunavut (83% versus 47%). This study is an essential first step toward describing a Model of Care for forensic psychiatry patients in circumpolar regions; furthermore, the clinical similarities between the two populations provide support for future joint Arctic research and the inclusion of artic forensic patients in international studies.

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 score0.270
Threshold uncertainty score0.543

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0040.002
Scholarly communication0.0010.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.015
GPT teacher head0.328
Teacher spread0.312 · 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

Citations4
Published2023
Admission routes2
Has abstractyes

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