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Record W2528092513 · doi:10.5430/jnep.v7n2p99

Coping strategies as predictors of coursework stress among university nursing students

2016· article· en· W2528092513 on OpenAlexvenueno aff
Salwa Hassanein, Inass Helmy Elshair, Amany Abdrbo, Eman Gaber Hassan

Bibliographic record

VenueJournal of Nursing Education and Practice · 2016
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare professionals’ stress and burnout
Canadian institutionsnot available
Fundersnot available
KeywordsCourseworkStressorWishful thinkingCoping (psychology)PsychologyNursingDescriptive researchClinical psychologyMedical educationMedicineSocial psychologyPedagogyMathematics

Abstract

fetched live from OpenAlex

For nursing students, coping with stress is a dynamic and continuous process. Students are affected by different kinds of stressors such as the pressure to achieve academically. It is important for students to develop coping strategies in order to succeed. The aims of this study are assessing nursing students' perceived level of university coursework stress and their coping strategies, describing the difference between male and female nursing students in that respect, and identifying coping strategies that can predict coursework stress levels. A descriptive, predictive study was conducted utilizing a sample of 96 nursing students. The participants were asked to fill a self-administered questionnaire about coping strategies. The conclusion of this study is that nursing students have moderate stress levels related to their academic coursework. Problem-solving strategies have the highest mean of the eight subscales; however, wishful thinking and tension reduction were the only significant coping mechanisms that worked as predictors of coursework stress.

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)0.005
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.090
GPT teacher head0.524
Teacher spread0.434 · 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

Citations3
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Nursing Education and Practice→Same topicHealthcare professionals’ stress and burnout→French-language works237,207→