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Record W2132430077 · doi:10.1027/0227-5910.27.1.31

Fragmented Pathways to Care

2006· article· en· W2132430077 on OpenAlexaff
Carol Strıke, Anne E. Rhodes, Yvonne Bergmans, Paul S. Links

Bibliographic record

VenueCrisis · 2006
Typearticle
Languageen
FieldPsychology
TopicMental Health Treatment and Access
Canadian institutionsSt. Michael's HospitalUniversity of TorontoCentre for Addiction and Mental Health
Fundersnot available
KeywordsMental healthQualitative researchPsychological interventionHealth careBorderline personality disorderPersonalityAddictionPsychiatryPsychologyMedicineNursingClinical psychologySocial psychology

Abstract

fetched live from OpenAlex

Using qualitative methods, this study examined how, and under what circumstances, suicidal men used mental health services. In particular, the analyses focused on fragmented pathways to care. Fifteen men with a history of suicidal and aggressive behaviors and a diagnosis of borderline personality disorder and/or antisocial personality disorder participated in semistructured interviews that consisted of questions about their mental health status and experiences with mental health and addiction services. Interviews were taped and transcribed. An iterative, inductive qualitative analytic process was used. Men followed a cyclical pattern wherein negative experiences with health care providers were said to be followed by avoidance of health care settings, crisis, and then by involuntary service utilization. Men identified five health care provider and three personal practices, and two types of episodes they believed to contribute to their fragmented pathways to care. Implementation of specialized interventions, and providing patients with more information and more opportunity to participate in decisions, may improve interactions between patients and providers and improve patients' mental health status.

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)0.013
metaresearch head score (Gemma)0.036
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 score0.013
Threshold uncertainty score0.070

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.036
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0060.008
Scholarly communication0.0070.009
Open science0.0020.012
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.029
GPT teacher head0.350
Teacher spread0.321 · 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

Citations74
Published2006
Admission routes1
Has abstractyes

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