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Record W1926780109 · doi:10.1080/14999013.2015.1073195

Patients with Mental Health Issues in the Emergency Department: The Relationship Between Coercion and Perceptions of Being Helped, Psychologically Hurt, and Physically Harmed

2015· article· en· W1926780109 on OpenAlexaffabout
Natalie A. Harrison, Sarah Mordell, Ronald Roesch, Kelly Watt

Bibliographic record

VenueInternational Journal of Forensic Mental Health · 2015
Typearticle
Languageen
FieldPsychology
TopicHealthcare Decision-Making and Restraints
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsEmergency departmentMental healthFeelingMedicinePerceptionPopulationCoercion (linguistics)PsychiatryMedical emergencyPsychologyNursingSocial psychology

Abstract

fetched live from OpenAlex

Although patients with mental health issues are increasingly turning to emergency departments to receive mental health services, emergency department staff report being ill-equipped to assist this population. The purpose of this study was threefold. First, we wanted to understand how patients with mental health emergencies who are later admitted to psychiatric units perceived their experience in the emergency department, specifically whether they felt that their experience was helpful or harmful (physically or psychologically) and whether they felt like they were treated differently than patients with medical emergencies. Second, we wanted to understand whether these experiences were impacted by patients' perceptions that they were coerced into seeking treatment. Third, we wanted to gain patients' perspectives on how emergency departments could be modified to better accommodate mental health emergencies. We conducted interviews with 49 patients in an inpatient unit at a large general hospital in British Columbia, Canada, shortly after patients were triaged from the emergency department. We found that roughly half of patients endorsed high levels of feeling helped, with the other half endorsing low levels. Additionally, perceptions of having control over coming to the emergency department were predictive of patients' perceptions of being helped and psychologically hurt.

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)0.002
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 score0.095
Threshold uncertainty score0.289

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.067
GPT teacher head0.433
Teacher spread0.366 · 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

Citations10
Published2015
Admission routes2
Has abstractyes

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