MétaCan
Menu
Back to cohort
Record W2155188987 · doi:10.1080/14789949.2012.668214

A tale of two cultures: examining patient-centered care in a forensic mental health hospital

2012· article· en· W2155188987 on OpenAlexafffund
James Livingston, Alicia Nijdam‐Jones, Johann Brink

Bibliographic record

VenueJournal of Forensic Psychiatry and Psychology · 2012
Typearticle
Languageen
FieldArts and Humanities
TopicMental Health and Psychiatry
Canadian institutionsSimon Fraser UniversityBC Mental Health & Substance Use ServicesUniversity of British Columbia
FundersMental Health CommissionCanadian Health Services Research Foundation
KeywordsMental healthMental health serviceForensic scienceContext (archaeology)Forensic nursingMental health careHealth carePerceptionNursingPsychologyMental healthcareForensic psychiatryMedicinePsychiatry

Abstract

fetched live from OpenAlex

Several questions remain unanswered regarding the extent to which the principles and practices of patient-centered care are achievable in the context of a forensic mental health hospital. This study examined patient-centered care from the perspectives of patients and providers in a forensic mental health hospital. Patient-centered care was assessed using several measures of complementary constructs. Interviews were conducted with 30 patients and surveys were completed by 28 service providers in a forensic mental health hospital. Patients and providers shared similar views of the therapeutic milieu and recovery orientation of services; however, providers were more likely to perceive the hospital as being potentially unsafe. Overall, the findings indicated that characteristics of patient-centered care may be found within a forensic mental health hospital. The principles of patient-centered care can be integrated into service delivery in forensic mental health hospitals, though special attention to providers' perceptions of safety 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)0.024
metaresearch head score (Gemma)0.034
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.128

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.034
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0150.018
Scholarly communication0.0120.011
Open science0.0020.016
Research integrity0.0020.006
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 head0.027
GPT teacher head0.319
Teacher spread0.292 · 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 designQualitative
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

Citations83
Published2012
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Forensic Psychiatry and PsychologySame topicMental Health and PsychiatryFrench-language works237,207