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Record W4391263586 · doi:10.53379/cjcd.2024.373

Determining the Relationship Between Perceptions of the Nursing Profession and Attitudes towards Career Future of Nursing Senior Students: An Observational Study

2024· article· en· W4391263586 on OpenAlexvenueno aff
Kezban Koraş Sözen, Tuğba Aydemir

Bibliographic record

VenueCanadian Journal of Career Development · 2024
Typearticle
Languageen
FieldHealth Professions
TopicProblem Solving Skills Development
Canadian institutionsnot available
Fundersnot available
KeywordsObservational studyNursingPerceptionPsychologyMedicineMedical education

Abstract

fetched live from OpenAlex

This study was conducted to examine the relationship between nursing senior students' perceptions of the nursing profession and their attitudes toward their career future and to determine the factors affecting their career plans. The universe of the descriptive and relation-seeking study consisted of 143 senior students studying at the nursing department of a university. The study was completed with 105 students who met the inclusion criteria and agreed to participate. It was determined that CFI scores differed significantly according to the gender of the students, their readiness for the profession and the post-graduate employment statute. It was determined that there was a significant positive correlation between the CFI scale total score, career adaptability, career optimism sub-dimensions and the total score of PNPS. Also, it was determined that the sub-dimensions of age, gender, post-graduation work plan and PNPS were the variables explaining the students' career plans at 56%. It was determined that students' perceptions of the statute and the quality of the nursing profession were factors affecting their career plans. For this reason, it should be aimed to develop a positive professional perception by providing students with professional values ​​for the profession throughout nursing education.

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)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
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 head0.263
GPT teacher head0.463
Teacher spread0.200 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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Same venueCanadian Journal of Career DevelopmentSame topicProblem Solving Skills DevelopmentFrench-language works237,207