MétaCan
Menu
Back to cohort
Record W2141060950 · doi:10.1177/1074840714542875

Attitudes of Registered and Licensed Practical Nurses About the Importance of Families in Surgical Hospital Units

2014· article· en· W2141060950 on OpenAlexaboutno aff
Katrín Blöndal, Sigríður Zoëga, Jorunn E. Hafsteinsdottir, Olof Asdis Olafsdottir, Audur B. Thorvardardottir, Sigrun A. Hafsteinsdottir, Herdís Sveinsdóttir

Bibliographic record

VenueJournal of Family Nursing · 2014
Typearticle
Languageen
FieldHealth Professions
TopicFamily and Patient Care in Intensive Care Units
Canadian institutionsnot available
FundersFamily Process Institute
KeywordsMedicineRegistered nurseFamily medicineSurgical proceduresNursingPsychologySurgery

Abstract

fetched live from OpenAlex

The purpose of this study was to examine attitudes of registered nurses and licensed practical nurses about the importance of the family in surgical hospital units before (T1) and after (T2) implementation of a Family Systems Nursing educational intervention based on the Calgary Family Assessment and Intervention Models. This study was part of the Landspitali University Hospital Family Nursing Implementation Project and used a nonrandomized, quasi-experimental design with nonequivalent group before and after and without a control group. There were 181 participants at T1 and 130 at T2. No difference was found in nurses' attitudes as measured by the Families Importance in Nursing Care-Nurses' Attitudes (FINC-NA) questionnaire, before and after the educational intervention. Attitudes toward families were favorable at both times. Analysis of demographic variables showed that age, work experience, and workplace (inpatient vs. outpatient units) had an effect on the nurses' attitudes toward families. The influence of work experience on attitudes toward family care warrants further exploration.

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)0.003
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.138
GPT teacher head0.443
Teacher spread0.305 · 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 designQualitative
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

Citations57
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Family NursingSame topicFamily and Patient Care in Intensive Care UnitsFrench-language works237,207