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Record W2612952585 · doi:10.3233/wor-172540

Experiencing violence in a psychiatric setting: Generalized hypervigilance and the influence of caring in the fear experienced

2017· article· en· W2612952585 on OpenAlexaff
Lydia Forté, Nathalie Lanctôt, Steve Geoffrion, André Marchand, Stéphane Guay

Bibliographic record

VenueWork · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicWorkplace Violence and Bullying
Canadian institutionsUniversité du Québec à MontréalUniversité de MontréalInstitut Universitaire en Santé Mentale de Québec
Fundersnot available
KeywordsHypervigilancePsychologyPsychiatryClinical psychologyAnxiety

Abstract

fetched live from OpenAlex

BACKGROUND: Exposure to violence in the mental health sector both affects employees and has implications for the quality of care provided. OBJECTIVE: This phenomenological study aims to describe and understand the ways in which acts of aggression from a patient might affect workers in a psychiatric institute, their relationships with the patients and the services offered. METHODS: Two semi-structured interviews were conducted with each of the 15 participants from various professions within a psychiatric hospital. RESULTS: Our analysis reveals four themes: hypervigilance, caring, specific fear toward the aggressor and generalized fear of all patients. A state of hypervigilance is found among all participants. An emphasis on caring is present among the majority and unfolds as a continuum, ranging from being highly caring to showing little or no caring. A feeling of fear is expressed and is influenced by the participant's place on the caring continuum. Caring workers developed a specific fear of their aggressor, whereas those showing little or no caring developed a generalized fear of all patients. Following a violent event, caring participants maintained this outlook, whereas those demonstrating little to no caring were more inclined to disinvest from all patients. CONCLUSIONS: Hypervigilance and fear caused by experiences of violence impact the quality of care provided. Considerable interest should thus be paid to caring, which can influence fear and its effects.

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)0.001
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 score0.044
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.015
GPT teacher head0.305
Teacher spread0.290 · 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

Citations18
Published2017
Admission routes1
Has abstractyes

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