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Record W2166612973 · doi:10.1177/1054773809341730

Patient Demographics and Learning Needs: Examination of Relationship

2009· article· en· W2166612973 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueClinical Nursing Research · 2009
Typearticle
Languageen
FieldMedicine
TopicCardiac Health and Mental Health
Canadian institutionsToronto Metropolitan University
FundersCanadian Institutes of Health Research
KeywordsDemographicsMedicinePsychological interventionPatient educationFamily medicineNursingDemography

Abstract

fetched live from OpenAlex

BACKGROUND: Limited research has examined differences in patients' learning needs in relation to demographic characteristics, such as age, gender, level of education, and culture. Yet such knowledge is essential to develop postoperative educational interventions that are tailored to patients' needs. STUDY PURPOSE: The purpose of this study was to examine the relationship between learning needs and the demographic characteristics of patients who have undergone coronary artery bypass graft (CABG) surgery. METHOD: A descriptive design was used.The sample of convenience included 38 patients who met eligibility criteria. MAJOR RESULTS: Statistically significant relationships were found between the patients' age, gender, and cultural background, and learning needs (p<.05) and not between the learning needs and level of education. APPLICATION: These preliminary highlight the importance of attending to learning needs of patients with different backgrounds in order to improve self-management following CABG surgery.

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)0.005
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.783
Threshold uncertainty score0.526

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.004
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 integrity0.0000.001
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 head0.547
Teacher spread0.352 · 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