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Record W2299922362 · doi:10.1177/2333393616630465

An Interpretation of Nurse–Patient Relationships in Inpatient Psychiatry

2016· article· en· W2299922362 on OpenAlexaff
Catherine Thibeault

Bibliographic record

VenueGlobal Qualitative Nursing Research · 2016
Typearticle
Languageen
FieldPsychology
TopicCounseling, Therapy, and Family Dynamics
Canadian institutionsTrent University
Fundersnot available
KeywordsNarrativeDistressInterpretation (philosophy)Theme (computing)NursingPsychologyMedicineHermeneutic phenomenologyConstruct (python library)Mental healthLived experiencePsychotherapist

Abstract

fetched live from OpenAlex

Nurses who work in acute inpatient psychiatry, where lengths of stay are increasingly shortened, struggle to establish therapeutic nurse-patient relationships. The purpose of this inquiry was to illuminate the nature of relationships between inpatient psychiatric mental health (PMH) nurses and their patients. The author used semistructured interviews and nonparticipant observation in an interpretive phenomenological inquiry. The data consisted of texts that were transcribed from narratives and observations. The meanings that were generated led to the uncovering of patterns of commonality, or themes. Of the themes uncovered, the theme of mindful approach highlighted PMH nurses as engaging with patients in distress, strategically creating encounters to establish a basis for ongoing therapeutic work. The PMH nurse-patient relationship in acute inpatient psychiatry continues to be under pressure, but nurses still carefully construct relational approaches in response to patient distress, and patients in these settings experience these approaches as meaningful to their recovery.

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)0.003
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 score0.127
Threshold uncertainty score0.517

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.098
GPT teacher head0.512
Teacher spread0.414 · 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

Citations12
Published2016
Admission routes1
Has abstractyes

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