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Record W2943020294 · doi:10.5737/23688076292123131

https://canadianoncologynursingjournal.com/index.php/conj/article/view/982

2019· article· en· W2943020294 on OpenAlexaffvenue
Cheryl Page, Charissa Cordon, Jiahui Wong

Bibliographic record

VenueCanadian Oncology Nursing Journal · 2019
Typearticle
Languageen
FieldMedicine
TopicEmpathy and Medical Education
Canadian institutionsHamilton Health SciencesJuravinski HospitalMcMaster University Medical CentreUniversity Health Network
Fundersnot available
KeywordsMnemonicDocumentationRecallIntervention (counseling)MedicineComprehensionNursingHealth carePatient educationPsychologyMedical educationComputer science

Abstract

fetched live from OpenAlex

Effective patient education can influence cost savings and improve patient outcomes (CCO, 2006). Nursing staff provide education to patients and families through the assessment of learning needs, incorporating the teach-back method to assess comprehension, and documenting the care provided. For this pilot study, an educational intervention was developed incorporating a mnemonic memory aid to support a consistent, standardized approach in delivering effective patient teaching. Forty-five hematology nurses from Hamilton Health Sciences participated in the study, of which 36 completed the follow-up assessments. The mnemonic aid "CARE", developed for this study, helped nurses to recall the steps involved in patient education. The improved knowledge and the use of the mnemonic aid in patient education was sustained over the three- to six-weeks follow-up period. While there was an increase in documentation of the patient education after the intervention, the changes did not reach the statistically significant level. Further research on the use of mnemonics in nursing education would complement this pilot study.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.627
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.017
GPT teacher head0.334
Teacher spread0.316 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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
Published2019
Admission routes2
Has abstractyes

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