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Record W2062173344 · doi:10.1515/ijnes-2013-0086

A Guest in the House: Nursing Instructors’ Experiences of the Moral Distress Felt by Students during Inpatient Psychiatric Clinical Rotations

2014· article· en· W2062173344 on OpenAlexaff
Bernadine Wojtowicz, Brad Hagen

Bibliographic record

VenueInternational Journal of Nursing Education Scholarship · 2014
Typearticle
Languageen
FieldHealth Professions
TopicEthics in medical practice
Canadian institutionsUniversity of Lethbridge
Fundersnot available
KeywordsNursingDistressPsychologyMedicinePsychiatryPsychotherapist

Abstract

fetched live from OpenAlex

Significant research has been done on the impact of moral distress among nurses, particularly in acute and intensive care settings. However, little research to date has investigated the experiences that nursing students have with moral distress. Additionally, there is a dearth of research on the role of nursing instructors' perceptions of their responsibilities to their students when encountering morally distressing situations. This manuscript describes a qualitative study conducted with eight mental health nursing instructors who acknowledged a responsibility for helping students deal with moral distress and ethical issues, but who also struggled with ways to do so. Additionally, instructors expressed frustration with their "guest" status on inpatient psychiatric units and their powerlessness to effect moral change in a medical model of psychiatric care.

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)0.006
metaresearch head score (Gemma)0.025
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 score0.007
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.025
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0070.006
Scholarly communication0.0050.003
Open science0.0010.007
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0020.000

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 head0.138
GPT teacher head0.588
Teacher spread0.450 · 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

Citations8
Published2014
Admission routes1
Has abstractyes

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