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Record W2072715467 · doi:10.5430/jnep.v4n3p188

Attitudes toward caring for dying patients: An overview among Italian nursing students and preliminary psychometrics of the FATCOD-B scale

2013· article· en· W2072715467 on OpenAlexvenueno aff
Paolo Leombruni, Marco Miniotti, Andrea Bovero, Francesca Zizzi, Lorys Castelli, Riccardo Torta

Bibliographic record

VenueJournal of Nursing Education and Practice · 2013
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsnot available
Fundersnot available
KeywordsCronbach's alphaScale (ratio)CurriculumNursingDescriptive statisticsPsychometricsInternal consistencyPsychologyTest (biology)Nurse educationConsistency (knowledge bases)MedicineClinical psychologyPedagogy

Abstract

fetched live from OpenAlex

Background : Extensive research indicated that nursing students at the end of their curricula feel unprepared to care for the dying. Therefore, studies on nursing students’ attitudes to caring for dying patients play a key role in nursing education, and the FATCOD-B scale is the only tool that specifically evaluates them. Methods : A cross-sectional study design was used. During 2013, the FATCOD-B scale was administered to a sample of 82 nursing students. Descriptive statistics, the Student’s t -test, Cronbach’s alpha and principal components analysis were used in data analyses. Results: Italian nursing students’ scores on the FATCOD-B scale seemed to be lower than literature evidence on sums of ratings; however, mean ratings revealed similar levels of attitudes to the dying. Gender and personal experience with dying persons were not predictors of FATCOD-B scores. Internal consistency of the FATCOD-B scale was not satisfactory. Principal component analysis found a four-factor questionable solution for the FATCOD-B scale. Conclusions: Findings from the present study suggest a need for end-of-life care nursing education in Italy. The preliminary results concerning the psychometrics of the scale suggest that the Italian version of the FATCOD-B could be in need of revision. The implications for practice are discussed.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.179
Threshold uncertainty score0.243

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.323
GPT teacher head0.547
Teacher spread0.225 · 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 teacher head, 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

Citations44
Published2013
Admission routes1
Has abstractyes

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