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Record W6906421765 · doi:10.17483/2368

Sense of coherence, a worthy factor toward nursing student and new graduate satisfaction with nursing, goal setting affinities, and coping tendencies

2018· article· en· W6906421765 on OpenAlexaff

Bibliographic record

VenueVIURRSpace (Vancouver Island University) · 2018
Typearticle
Languageen
FieldNursing
TopicNursing education and management
Canadian institutionsVancouver Island University
Fundersnot available
KeywordsBurnoutFeelingCoping (psychology)StressorAttritionThrivingAttendanceMentorship

Abstract

fetched live from OpenAlex

Nursing student readiness for practice is a relevant topic for educators aimed to ready students for a difficult practice environment, and healthcare employers challenged with the high attrition rates of new graduates. The literature suggests that stressors toward burnout may begin in the undergraduate setting with student nurses experiencing feelings of burnout being at significantly higher risk of leaving their position after only 10 to 15 months (Rudman & Gustavsson, 2012; Rudman, Gustavsson, & Hultell, 2014). Readiness for practice as a student informs how new graduate nurses will come into the practice environment. Their sense of coherence, ability to set and achieve goals, and coping skills are important factors toward surviving and thriving in their place of work. This study includes fourth-year nursing students on their final day of school, standing at the threshold of their nursing careers. The purpose of this study was to investigate the relationship between sense of coherence scores of nursing students upon completion of their undergraduate program with their level of satisfaction in nursing as a career choice, coping skills, and goal setting tendencies.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.391
Threshold uncertainty score0.893

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.026
GPT teacher head0.263
Teacher spread0.237 · 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 designNot applicable
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

Citations5
Published2018
Admission routes1
Has abstractyes

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