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Record W3031741489 · doi:10.1177/0193945920923079

Development and Testing of a Measure of Self-awareness Among Nurses

2020· article· en· W3031741489 on OpenAlex

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

VenueWestern Journal of Nursing Research · 2020
Typearticle
Languageen
FieldNursing
TopicHealthcare Education and Workforce Issues
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsCronbach's alphaScale (ratio)Self-awarenessNursingPsychologyContent validityPsychometricsMedicineClinical psychologySocial psychology

Abstract

fetched live from OpenAlex

Self-awareness is an essential nursing competency and there is limited knowledge about nurses' levels and application of self-awareness and instruments to measure nursing-specific self-awareness. Using mixed methods, we developed and tested a scale to measure nurses' self-awareness. First, 13 nurses were interviewed to understand their meanings of self-awareness and to develop nursing-specific self-awareness scale. Qualitative analysis generated professional, personal, contextual, and contentious aspects of self-awareness. Second, a 25-item scale assessed through expert consultations and pilot testing with 252 nurses. The content validity index was 0.94. After psychometric testing, seven items were deleted. Cronbach's alpha for the 18-item scale was 0.87 and the four-factor structure accounted for 45.55% of the variance. Lastly, the final scale was administered to 216 nurses. Nurses' had moderate self-awareness (59.65 ± 7.01), significantly associated with age and years of the clinical and educational experience. Intensive care nurses were more self-aware than nurses in other settings.

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)0.002
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 score0.227
Threshold uncertainty score0.380

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.268
GPT teacher head0.476
Teacher spread0.208 · 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