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Quality of Nursing Diagnoses: Evaluation of an Educational Intervention

2005· article· en· W2166786858 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

VenueInternational Journal of Nursing Terminologies and Classifications · 2005
Typearticle
Languageen
FieldNursing
TopicNursing Diagnosis and Documentation
Canadian institutionsUniversity of Alberta
FundersSave Our Seas Foundation
KeywordsMedical diagnosisMedicineNursingNursing diagnosisNursing Outcomes ClassificationDocumentationQuality (philosophy)Intervention (counseling)Scale (ratio)Nurse educationFamily medicinePrimary nursingComputer sciencePathology

Abstract

fetched live from OpenAlex

PURPOSE: To investigate the effects on the quality of nursing diagnostic statements in patient records after education in the nursing process and implementation of new forms for recording. METHODS: Quasi-experimental design. Randomly selected patient records reviewed before and after intervention from one experimental unit (n = 70) and three control units (n = 70). A scale with 14 characteristics pertaining to nursing diagnoses was developed and used together with the instrument (CAT-CH-ING) for record review. FINDINGS: Quality of nursing diagnostic statements improved in the experimental unit, whereas no improvement was found in the control units. Serious flaws in the use of the etiology component were found. CONCLUSION. Nurses must be more concerned with the accuracy and quality of the nursing diagnoses and the etiology component needs to be given special attention. PRACTICE IMPLICATIONS: Education of RNs in nursing diagnostic statements and peer review using standardized evaluation instruments can be means to further enhance RNs' documentation practice.

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)0.001
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.966
Threshold uncertainty score0.522

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.194
GPT teacher head0.509
Teacher spread0.314 · 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