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Record W2160775971 · doi:10.5430/jha.v1n1p21

Effects of a web-based preoperative education program for patients undergoing ambulatory surgery: a preliminary study

2012· article· en· W2160775971 on OpenAlexvenueno aff
Eun‐Shim Nahm, Lena Stevens, Pamela Scott, Kristy Gorman

Bibliographic record

VenueJournal of Hospital Administration · 2012
Typearticle
Languageen
FieldPsychology
TopicMusic Therapy and Health
Canadian institutionsnot available
Fundersnot available
KeywordsAmbulatoryMedicineAmbulatory carePatient educationPatient satisfactionPatient careTertiary careNursingFamily medicineSurgeryHealth care

Abstract

fetched live from OpenAlex

Increasing numbers of surgical procedures that were once done in hospitals are now being performed in ambulatory care settings. Provision of quality preoperative education in those settings has become a challenge. This article reports findings from a practice-based study where the nurses in a preoperative preparation center implemented a supplemental, web-based educational program for same-day surgery patients and assessed its outcomes (N = 69). The patients who used the web-based program in addition to usual care achieved significantly higher scores for anesthesia knowledge (t = 2.15, p = 0.04) and teaching satisfaction (t = 2.13, p = 0.04) than those who received usual care only. The findings demonstrate a great potential for use of web-based programs to improve patient education in busy preoperative care areas. A convenience sample with a small sample size was a major limitation. Further studies with large samples are needed to demonstrate tangible clinical outcomes.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.017
GPT teacher head0.345
Teacher spread0.329 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations9
Published2012
Admission routes1
Has abstractyes

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