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Record W4387893849 · doi:10.1177/10547738231206610

Self-Deception in Clinical Nursing Practice: A Concept Analysis

2023· article· en· W4387893849 on OpenAlex
Granville Eric Miller, Dave Holmes

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueClinical Nursing Research · 2023
Typearticle
Languageen
FieldHealth Professions
TopicEthics in medical practice
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsDeceptionCognitive dissonancePhenomenonPsychologyCoping (psychology)DistressNursingContext (archaeology)Social psychologyMedicinePsychotherapistEpistemology

Abstract

fetched live from OpenAlex

In this paper, we explore the phenomenon of "self-deception" within the context of nursing, focusing on how nurses employ this coping mechanism when faced with dissonance, distress, and conflicting situations in clinical settings. Our primary objective is to examine the phenomenon of self-deception using Rodgers' evolutionary method of concept analysis. Focusing on nurses' experiences in challenging situations, our analysis highlights how self-deception is often employed as a coping strategy. According to our conceptual analysis, self-deception in nursing clinical practice highlights tensions between different paradigms and expectations in healthcare settings. These tensions stem from the power dynamics and subservience that nurses often face, which can hinder their ability to advocate for themselves, their patients, and the nursing profession.

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.

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)0.199
metaresearch head score (Gemma)0.380
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch, Science and technology studies, Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.676
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1990.380
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.009
Science and technology studies0.0020.004
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0020.033
Insufficient payload (model declined to judge)0.0010.006

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 head0.523
GPT teacher head0.761
Teacher spread0.238 · 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