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Record W2053462808 · doi:10.1177/1557988314528236

Male ICU Nurses’ Experiences of Taking Care of Dying Patients and Their Families

2014· article· en· W2053462808 on OpenAlexaff
Tammy W. Wu, John L. Oliffe, Vicky Bungay, Joy L. Johnson

Bibliographic record

VenueAmerican Journal of Men s Health · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicGender Roles and Identity Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSocial connectednessFeelingPsychologyRecreationCoping (psychology)NursingContext (archaeology)Intensive care unitSocial psychologyMedicineClinical psychologyPsychiatry

Abstract

fetched live from OpenAlex

Male intensive care unit (ICU) nurses bring energy and expertise along with an array of beliefs and practices to their workplace. This article investigates the experiences of male ICU nurses in the context of caring for dying patients and their families. Applying a gender analysis, distilled are insights to how masculinities inform and influence the participants' practices and coping strategies. The findings reveal participants draw on masculine ideals of being a protector and rational in their decisive actions toward meeting the comfort needs of dying patients and their families. Somewhat paradoxically, most participants also transgressed masculine norms by outwardly expressing their feelings and talking about emotions related to these experiences. Participants also reported renewed appreciation of their life and their families and many men chronicled recreational activities and social connectedness as strategies for coping with workplace induced stresses. The findings drawn from this study can guide both formal and informal support services for men who are ICU nurses, which in turn might aid retention of this subgroup of workers.

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)0.001
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.266
Threshold uncertainty score0.754

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.015
GPT teacher head0.315
Teacher spread0.300 · 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 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

Citations20
Published2014
Admission routes1
Has abstractyes

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